Overview

Dataset statistics

Number of variables111
Number of observations491
Missing cells14331
Missing cells (%)26.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory328.6 KiB
Average record size in memory685.3 B

Variable types

UNSUPPORTED35
CAT33
BOOL31
NUM9
URL2
PATH1

Warnings

subreddit has constant value "491" Constant
selftext has constant value "491" Constant
saved has constant value "491" Constant
clicked has constant value "491" Constant
subreddit_name_prefixed has constant value "491" Constant
hidden has constant value "491" Constant
pwls has constant value "491" Constant
downs has constant value "491" Constant
quarantine has constant value "491" Constant
link_flair_text_color has constant value "491" Constant
subreddit_type has constant value "491" Constant
is_original_content has constant value "491" Constant
is_meta has constant value "491" Constant
can_mod_post has constant value "491" Constant
edited has constant value "491" Constant
is_self has constant value "491" Constant
wls has constant value "491" Constant
suggested_sort has constant value "491" Constant
archived has constant value "491" Constant
is_crosspostable has constant value "491" Constant
pinned has constant value "491" Constant
over_18 has constant value "491" Constant
media_only has constant value "491" Constant
can_gild has constant value "491" Constant
spoiler has constant value "491" Constant
locked has constant value "491" Constant
visited has constant value "491" Constant
subreddit_id has constant value "491" Constant
link_flair_background_color has constant value "491" Constant
is_robot_indexable has constant value "491" Constant
whitelist_status has constant value "491" Constant
contest_mode has constant value "491" Constant
author_patreon_flair has constant value "491" Constant
parent_whitelist_status has constant value "491" Constant
stickied has constant value "491" Constant
is_video has constant value "491" Constant
author_fullname has a high cardinality: 171 distinct values High cardinality
thumbnail has a high cardinality: 434 distinct values High cardinality
domain has a high cardinality: 149 distinct values High cardinality
author_flair_text has a high cardinality: 55 distinct values High cardinality
author has a high cardinality: 171 distinct values High cardinality
score is highly correlated with upsHigh correlation
ups is highly correlated with scoreHigh correlation
created_utc is highly correlated with createdHigh correlation
created is highly correlated with created_utcHigh correlation
author_flair_css_class is highly correlated with author_flair_template_id and 1 other fieldsHigh correlation
author_flair_template_id is highly correlated with author_flair_css_class and 1 other fieldsHigh correlation
author_flair_text is highly correlated with author_flair_template_id and 3 other fieldsHigh correlation
author_flair_type is highly correlated with author_flair_textHigh correlation
author_flair_text_color is highly correlated with author_flair_textHigh correlation
link_flair_template_id is highly correlated with link_flair_css_class and 1 other fieldsHigh correlation
link_flair_css_class is highly correlated with link_flair_template_idHigh correlation
link_flair_text is highly correlated with link_flair_template_idHigh correlation
approved_at_utc has 491 (100.0%) missing values Missing
mod_reason_title has 491 (100.0%) missing values Missing
link_flair_css_class has 8 (1.6%) missing values Missing
thumbnail_height has 45 (9.2%) missing values Missing
top_awarded_type has 491 (100.0%) missing values Missing
author_flair_background_color has 203 (41.3%) missing values Missing
thumbnail_width has 45 (9.2%) missing values Missing
author_flair_template_id has 440 (89.6%) missing values Missing
secure_media has 488 (99.4%) missing values Missing
category has 491 (100.0%) missing values Missing
link_flair_text has 8 (1.6%) missing values Missing
approved_by has 491 (100.0%) missing values Missing
author_flair_css_class has 437 (89.0%) missing values Missing
post_hint has 47 (9.6%) missing values Missing
content_categories has 491 (100.0%) missing values Missing
mod_note has 491 (100.0%) missing values Missing
removed_by_category has 491 (100.0%) missing values Missing
banned_by has 491 (100.0%) missing values Missing
selftext_html has 491 (100.0%) missing values Missing
likes has 491 (100.0%) missing values Missing
banned_at_utc has 491 (100.0%) missing values Missing
view_count has 491 (100.0%) missing values Missing
preview has 47 (9.6%) missing values Missing
author_flair_text has 152 (31.0%) missing values Missing
removed_by has 491 (100.0%) missing values Missing
num_reports has 491 (100.0%) missing values Missing
distinguished has 491 (100.0%) missing values Missing
mod_reason_by has 491 (100.0%) missing values Missing
removal_reason has 491 (100.0%) missing values Missing
report_reasons has 491 (100.0%) missing values Missing
discussion_type has 491 (100.0%) missing values Missing
author_flair_text_color has 152 (31.0%) missing values Missing
media has 488 (99.4%) missing values Missing
link_flair_template_id has 484 (98.6%) missing values Missing
is_gallery has 489 (99.6%) missing values Missing
media_metadata has 489 (99.6%) missing values Missing
gallery_data has 489 (99.6%) missing values Missing
title has unique values Unique
name has unique values Unique
id has unique values Unique
permalink has unique values Unique
approved_at_utc is an unsupported type, check if it needs cleaning or further analysis Unsupported
mod_reason_title is an unsupported type, check if it needs cleaning or further analysis Unsupported
link_flair_richtext is an unsupported type, check if it needs cleaning or further analysis Unsupported
top_awarded_type is an unsupported type, check if it needs cleaning or further analysis Unsupported
media_embed is an unsupported type, check if it needs cleaning or further analysis Unsupported
user_reports is an unsupported type, check if it needs cleaning or further analysis Unsupported
secure_media is an unsupported type, check if it needs cleaning or further analysis Unsupported
category is an unsupported type, check if it needs cleaning or further analysis Unsupported
secure_media_embed is an unsupported type, check if it needs cleaning or further analysis Unsupported
approved_by is an unsupported type, check if it needs cleaning or further analysis Unsupported
author_flair_richtext is an unsupported type, check if it needs cleaning or further analysis Unsupported
gildings is an unsupported type, check if it needs cleaning or further analysis Unsupported
content_categories is an unsupported type, check if it needs cleaning or further analysis Unsupported
mod_note is an unsupported type, check if it needs cleaning or further analysis Unsupported
removed_by_category is an unsupported type, check if it needs cleaning or further analysis Unsupported
banned_by is an unsupported type, check if it needs cleaning or further analysis Unsupported
selftext_html is an unsupported type, check if it needs cleaning or further analysis Unsupported
likes is an unsupported type, check if it needs cleaning or further analysis Unsupported
banned_at_utc is an unsupported type, check if it needs cleaning or further analysis Unsupported
view_count is an unsupported type, check if it needs cleaning or further analysis Unsupported
preview is an unsupported type, check if it needs cleaning or further analysis Unsupported
all_awardings is an unsupported type, check if it needs cleaning or further analysis Unsupported
awarders is an unsupported type, check if it needs cleaning or further analysis Unsupported
treatment_tags is an unsupported type, check if it needs cleaning or further analysis Unsupported
removed_by is an unsupported type, check if it needs cleaning or further analysis Unsupported
num_reports is an unsupported type, check if it needs cleaning or further analysis Unsupported
distinguished is an unsupported type, check if it needs cleaning or further analysis Unsupported
mod_reason_by is an unsupported type, check if it needs cleaning or further analysis Unsupported
removal_reason is an unsupported type, check if it needs cleaning or further analysis Unsupported
report_reasons is an unsupported type, check if it needs cleaning or further analysis Unsupported
discussion_type is an unsupported type, check if it needs cleaning or further analysis Unsupported
mod_reports is an unsupported type, check if it needs cleaning or further analysis Unsupported
media is an unsupported type, check if it needs cleaning or further analysis Unsupported
media_metadata is an unsupported type, check if it needs cleaning or further analysis Unsupported
gallery_data is an unsupported type, check if it needs cleaning or further analysis Unsupported
ups has 68 (13.8%) zeros Zeros
total_awards_received has 354 (72.1%) zeros Zeros
score has 68 (13.8%) zeros Zeros
num_comments has 12 (2.4%) zeros Zeros
num_crossposts has 417 (84.9%) zeros Zeros

Reproduction

Analysis started2021-01-12 12:52:22.485222
Analysis finished2021-01-12 12:52:48.306715
Duration25.82 seconds
Software versionpandas-profiling v2.10.0
Download configurationconfig.yaml

Variables

approved_at_utc
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

subreddit
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Conservative
491 

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters5892
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowConservative
2nd rowConservative
3rd rowConservative
4th rowConservative
5th rowConservative
ValueCountFrequency (%)
Conservative491
100.0%
2021-01-12T20:52:48.450327image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:48.507179image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
conservative491
100.0%

Most occurring characters

ValueCountFrequency (%)
e982
16.7%
v982
16.7%
C491
8.3%
o491
8.3%
n491
8.3%
s491
8.3%
r491
8.3%
a491
8.3%
t491
8.3%
i491
8.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5401
91.7%
Uppercase Letter491
 
8.3%

Most frequent character per category

ValueCountFrequency (%)
e982
18.2%
v982
18.2%
o491
9.1%
n491
9.1%
s491
9.1%
r491
9.1%
a491
9.1%
t491
9.1%
i491
9.1%
ValueCountFrequency (%)
C491
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5892
100.0%

Most frequent character per script

ValueCountFrequency (%)
e982
16.7%
v982
16.7%
C491
8.3%
o491
8.3%
n491
8.3%
s491
8.3%
r491
8.3%
a491
8.3%
t491
8.3%
i491
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII5892
100.0%

Most frequent character per block

ValueCountFrequency (%)
e982
16.7%
v982
16.7%
C491
8.3%
o491
8.3%
n491
8.3%
s491
8.3%
r491
8.3%
a491
8.3%
t491
8.3%
i491
8.3%

selftext
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
491 

Length

Max length0
Median length0
Mean length0
Min length0

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
491
100.0%
2021-01-12T20:52:48.649798image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:48.703654image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

author_fullname
Categorical

HIGH CARDINALITY

Distinct171
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
t2_4hgotpz8
53 
t2_avcps
45 
t2_hyfa9
 
23
t2_1i0qmyxf
 
15
t2_5c1yipoz
 
14
Other values (166)
341 

Length

Max length11
Median length11
Mean length9.710794297
Min length8

Characters and Unicode

Total characters4768
Distinct characters37
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)23.0%

Sample

1st rowt2_4hgotpz8
2nd rowt2_4hgotpz8
3rd rowt2_4u7bd
4th rowt2_d0rgw
5th rowt2_4hgotpz8
ValueCountFrequency (%)
t2_4hgotpz853
 
10.8%
t2_avcps45
 
9.2%
t2_hyfa923
 
4.7%
t2_1i0qmyxf15
 
3.1%
t2_5c1yipoz14
 
2.9%
t2_d0rgw14
 
2.9%
t2_x439212
 
2.4%
t2_i97an11
 
2.2%
t2_ykafq8t10
 
2.0%
t2_3k45wst010
 
2.0%
Other values (161)284
57.8%
2021-01-12T20:52:48.889158image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
t2_4hgotpz853
 
10.8%
t2_avcps45
 
9.2%
t2_hyfa923
 
4.7%
t2_1i0qmyxf15
 
3.1%
t2_5c1yipoz14
 
2.9%
t2_d0rgw14
 
2.9%
t2_x439212
 
2.4%
t2_i97an11
 
2.2%
t2_ykafq8t10
 
2.0%
t2_3k45wst010
 
2.0%
Other values (161)284
57.8%

Most occurring characters

ValueCountFrequency (%)
t613
 
12.9%
2578
 
12.1%
_491
 
10.3%
p168
 
3.5%
4159
 
3.3%
a150
 
3.1%
8136
 
2.9%
v125
 
2.6%
h119
 
2.5%
g117
 
2.5%
Other values (27)2112
44.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2731
57.3%
Decimal Number1546
32.4%
Connector Punctuation491
 
10.3%

Most frequent character per category

ValueCountFrequency (%)
t613
22.4%
p168
 
6.2%
a150
 
5.5%
v125
 
4.6%
h119
 
4.4%
g117
 
4.3%
y112
 
4.1%
q104
 
3.8%
s102
 
3.7%
o101
 
3.7%
Other values (16)1020
37.3%
ValueCountFrequency (%)
2578
37.4%
4159
 
10.3%
8136
 
8.8%
1110
 
7.1%
0108
 
7.0%
9108
 
7.0%
596
 
6.2%
389
 
5.8%
688
 
5.7%
774
 
4.8%
ValueCountFrequency (%)
_491
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2731
57.3%
Common2037
42.7%

Most frequent character per script

ValueCountFrequency (%)
t613
22.4%
p168
 
6.2%
a150
 
5.5%
v125
 
4.6%
h119
 
4.4%
g117
 
4.3%
y112
 
4.1%
q104
 
3.8%
s102
 
3.7%
o101
 
3.7%
Other values (16)1020
37.3%
ValueCountFrequency (%)
2578
28.4%
_491
24.1%
4159
 
7.8%
8136
 
6.7%
1110
 
5.4%
0108
 
5.3%
9108
 
5.3%
596
 
4.7%
389
 
4.4%
688
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII4768
100.0%

Most frequent character per block

ValueCountFrequency (%)
t613
 
12.9%
2578
 
12.1%
_491
 
10.3%
p168
 
3.5%
4159
 
3.3%
a150
 
3.1%
8136
 
2.9%
v125
 
2.6%
h119
 
2.5%
g117
 
2.5%
Other values (27)2112
44.3%

saved
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:48.951989image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

mod_reason_title
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

gilded
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
0
484 
1
 
6
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters491
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0484
98.6%
16
 
1.2%
21
 
0.2%
2021-01-12T20:52:49.222266image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:49.280112image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
0484
98.6%
16
 
1.2%
21
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0484
98.6%
16
 
1.2%
21
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number491
100.0%

Most frequent character per category

ValueCountFrequency (%)
0484
98.6%
16
 
1.2%
21
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common491
100.0%

Most frequent character per script

ValueCountFrequency (%)
0484
98.6%
16
 
1.2%
21
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII491
100.0%

Most frequent character per block

ValueCountFrequency (%)
0484
98.6%
16
 
1.2%
21
 
0.2%

clicked
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:49.328980image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

title
Categorical

UNIQUE

Distinct491
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Parler Sues Amazon for Site Takedown, Citing Antitrust Violation
 
1
H.R.127 - 117th Congress(2021-2022): To provide for the licensing of firearm and ammunition possession and the registration of firearms, and to prohibit the possession of certain ammunition.
 
1
Californians should fire Gavin Newsom while they still have a state to save
 
1
Antifa's Determined to Prevent a Book About Their Tactics From Being Published
 
1
Secret Service Investigating Death Threats Made Against Mike Pence - Look Who Made Them
 
1
Other values (486)
486 

Length

Max length298
Median length77
Mean length84.47861507
Min length15

Characters and Unicode

Total characters41479
Distinct characters90
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique491 ?
Unique (%)100.0%

Sample

1st rowParler finds refuge with right-leaning webhosting service
2nd rowElon Musk: A lot of people are going to be super unhappy with West Coast high tech as the de facto arbiter of free speech
3rd rowSorry Cleveland
4th rowDemocrat Law Professor: Trump Never Actually Called for Violence or a Riot
5th rowElon Musk Advises People to Ditch Facebook and Use Signal
ValueCountFrequency (%)
Parler Sues Amazon for Site Takedown, Citing Antitrust Violation1
 
0.2%
H.R.127 - 117th Congress(2021-2022): To provide for the licensing of firearm and ammunition possession and the registration of firearms, and to prohibit the possession of certain ammunition.1
 
0.2%
Californians should fire Gavin Newsom while they still have a state to save1
 
0.2%
Antifa's Determined to Prevent a Book About Their Tactics From Being Published1
 
0.2%
Secret Service Investigating Death Threats Made Against Mike Pence - Look Who Made Them1
 
0.2%
US double standards on Capitol riot and HK turmoil ‘will backfire with endless internal struggles’1
 
0.2%
Biden says Cruz, Hawley part of ‘big lie’ -- while senators claim they are being called Nazis1
 
0.2%
AOC: "Free advice - if you are losing tens of thousands of followers the moment Twitter starts taking down Neo-Nazis and violent insurrectionists, maybe don’t advertise that!"1
 
0.2%
Big Tech Oligarchs Collude To Ban Parler From Internet And Phones -- No such widespread censorship was cast upon leftist elites who encouraged the repeated outbreak of deadly riots last year.1
 
0.2%
Save the Constitution From Big Tech1
 
0.2%
Other values (481)481
98.0%
2021-01-12T20:52:49.529444image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
to193
 
3.0%
the174
 
2.7%
of161
 
2.5%
trump123
 
1.9%
for92
 
1.4%
and72
 
1.1%
in70
 
1.1%
capitol61
 
0.9%
on55
 
0.8%
twitter54
 
0.8%
Other values (2379)5445
83.8%

Most occurring characters

ValueCountFrequency (%)
6009
14.5%
e3701
 
8.9%
o2628
 
6.3%
t2481
 
6.0%
i2387
 
5.8%
a2281
 
5.5%
n2217
 
5.3%
r2196
 
5.3%
s2149
 
5.2%
l1417
 
3.4%
Other values (80)14013
33.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter30122
72.6%
Space Separator6009
 
14.5%
Uppercase Letter3963
 
9.6%
Other Punctuation772
 
1.9%
Decimal Number269
 
0.6%
Dash Punctuation127
 
0.3%
Final Punctuation117
 
0.3%
Initial Punctuation54
 
0.1%
Open Punctuation17
 
< 0.1%
Close Punctuation17
 
< 0.1%
Other values (2)12
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
e3701
12.3%
o2628
 
8.7%
t2481
 
8.2%
i2387
 
7.9%
a2281
 
7.6%
n2217
 
7.4%
r2196
 
7.3%
s2149
 
7.1%
l1417
 
4.7%
c995
 
3.3%
Other values (16)7670
25.5%
ValueCountFrequency (%)
T451
 
11.4%
C403
 
10.2%
A327
 
8.3%
P315
 
7.9%
S290
 
7.3%
B254
 
6.4%
D193
 
4.9%
R179
 
4.5%
I177
 
4.5%
M168
 
4.2%
Other values (15)1206
30.4%
ValueCountFrequency (%)
'238
30.8%
,187
24.2%
.151
19.6%
:104
13.5%
"40
 
5.2%
?13
 
1.7%
;10
 
1.3%
!7
 
0.9%
*6
 
0.8%
%5
 
0.6%
Other values (5)11
 
1.4%
ValueCountFrequency (%)
075
27.9%
153
19.7%
253
19.7%
525
 
9.3%
917
 
6.3%
412
 
4.5%
710
 
3.7%
38
 
3.0%
88
 
3.0%
68
 
3.0%
ValueCountFrequency (%)
-118
92.9%
5
 
3.9%
4
 
3.1%
ValueCountFrequency (%)
102
87.2%
15
 
12.8%
ValueCountFrequency (%)
36
66.7%
18
33.3%
ValueCountFrequency (%)
(16
94.1%
[1
 
5.9%
ValueCountFrequency (%)
)16
94.1%
]1
 
5.9%
ValueCountFrequency (%)
6009
100.0%
ValueCountFrequency (%)
|6
100.0%
ValueCountFrequency (%)
$6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin34085
82.2%
Common7394
 
17.8%

Most frequent character per script

ValueCountFrequency (%)
e3701
 
10.9%
o2628
 
7.7%
t2481
 
7.3%
i2387
 
7.0%
a2281
 
6.7%
n2217
 
6.5%
r2196
 
6.4%
s2149
 
6.3%
l1417
 
4.2%
c995
 
2.9%
Other values (41)11633
34.1%
ValueCountFrequency (%)
6009
81.3%
'238
 
3.2%
,187
 
2.5%
.151
 
2.0%
-118
 
1.6%
:104
 
1.4%
102
 
1.4%
075
 
1.0%
153
 
0.7%
253
 
0.7%
Other values (29)304
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII41297
99.6%
Punctuation182
 
0.4%

Most frequent character per block

ValueCountFrequency (%)
6009
14.6%
e3701
 
9.0%
o2628
 
6.4%
t2481
 
6.0%
i2387
 
5.8%
a2281
 
5.5%
n2217
 
5.4%
r2196
 
5.3%
s2149
 
5.2%
l1417
 
3.4%
Other values (73)13831
33.5%
ValueCountFrequency (%)
102
56.0%
36
 
19.8%
18
 
9.9%
15
 
8.2%
5
 
2.7%
4
 
2.2%
2
 
1.1%

link_flair_richtext
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size4.0 KiB

subreddit_name_prefixed
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
r/Conservative
491 

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters6874
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowr/Conservative
2nd rowr/Conservative
3rd rowr/Conservative
4th rowr/Conservative
5th rowr/Conservative
ValueCountFrequency (%)
r/Conservative491
100.0%
2021-01-12T20:52:49.716943image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:49.772827image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
r/conservative491
100.0%

Most occurring characters

ValueCountFrequency (%)
r982
14.3%
e982
14.3%
v982
14.3%
/491
7.1%
C491
7.1%
o491
7.1%
n491
7.1%
s491
7.1%
a491
7.1%
t491
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5892
85.7%
Other Punctuation491
 
7.1%
Uppercase Letter491
 
7.1%

Most frequent character per category

ValueCountFrequency (%)
r982
16.7%
e982
16.7%
v982
16.7%
o491
8.3%
n491
8.3%
s491
8.3%
a491
8.3%
t491
8.3%
i491
8.3%
ValueCountFrequency (%)
/491
100.0%
ValueCountFrequency (%)
C491
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6383
92.9%
Common491
 
7.1%

Most frequent character per script

ValueCountFrequency (%)
r982
15.4%
e982
15.4%
v982
15.4%
C491
7.7%
o491
7.7%
n491
7.7%
s491
7.7%
a491
7.7%
t491
7.7%
i491
7.7%
ValueCountFrequency (%)
/491
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6874
100.0%

Most frequent character per block

ValueCountFrequency (%)
r982
14.3%
e982
14.3%
v982
14.3%
/491
7.1%
C491
7.1%
o491
7.1%
n491
7.1%
s491
7.1%
a491
7.1%
t491
7.1%

hidden
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:49.801749image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

pwls
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
7
491 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters491
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7
2nd row7
3rd row7
4th row7
5th row7
ValueCountFrequency (%)
7491
100.0%
2021-01-12T20:52:49.940377image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:49.995230image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
7491
100.0%

Most occurring characters

ValueCountFrequency (%)
7491
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number491
100.0%

Most frequent character per category

ValueCountFrequency (%)
7491
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common491
100.0%

Most frequent character per script

ValueCountFrequency (%)
7491
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII491
100.0%

Most frequent character per block

ValueCountFrequency (%)
7491
100.0%

link_flair_css_class
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)0.6%
Missing8
Missing (%)1.6%
Memory size3.8 KiB
CONSERVATIVESONLY
477 
CONSERVATIVESONLY
 
5
 
1

Length

Max length18
Median length17
Mean length16.74745418
Min length0

Characters and Unicode

Total characters8223
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowCONSERVATIVESONLY
2nd rowCONSERVATIVESONLY
3rd rowCONSERVATIVESONLY
4th rowCONSERVATIVESONLY
5th rowCONSERVATIVESONLY
ValueCountFrequency (%)
CONSERVATIVESONLY477
97.1%
CONSERVATIVESONLY 5
 
1.0%
1
 
0.2%
(Missing)8
 
1.6%
2021-01-12T20:52:50.155802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:50.221627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
conservativesonly482
98.4%
nan8
 
1.6%

Most occurring characters

ValueCountFrequency (%)
O964
11.7%
N964
11.7%
S964
11.7%
E964
11.7%
V964
11.7%
C482
5.9%
R482
5.9%
A482
5.9%
T482
5.9%
I482
5.9%
Other values (5)993
12.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter8194
99.6%
Lowercase Letter24
 
0.3%
Space Separator5
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
O964
11.8%
N964
11.8%
S964
11.8%
E964
11.8%
V964
11.8%
C482
5.9%
R482
5.9%
A482
5.9%
T482
5.9%
I482
5.9%
Other values (2)964
11.8%
ValueCountFrequency (%)
n16
66.7%
a8
33.3%
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8218
99.9%
Common5
 
0.1%

Most frequent character per script

ValueCountFrequency (%)
O964
11.7%
N964
11.7%
S964
11.7%
E964
11.7%
V964
11.7%
C482
5.9%
R482
5.9%
A482
5.9%
T482
5.9%
I482
5.9%
Other values (4)988
12.0%
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8223
100.0%

Most frequent character per block

ValueCountFrequency (%)
O964
11.7%
N964
11.7%
S964
11.7%
E964
11.7%
V964
11.7%
C482
5.9%
R482
5.9%
A482
5.9%
T482
5.9%
I482
5.9%
Other values (5)993
12.1%

downs
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
0
491 
ValueCountFrequency (%)
0491
100.0%
2021-01-12T20:52:50.270495image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

thumbnail_height
Real number (ℝ≥0)

MISSING

Distinct43
Distinct (%)9.6%
Missing45
Missing (%)9.2%
Infinite0
Infinite (%)0.0%
Mean84.99327354
Minimum57
Maximum140
Zeros0
Zeros (%)0.0%
Memory size3.8 KiB
2021-01-12T20:52:50.334324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum57
5-th percentile70
Q173
median79
Q393
95-th percentile114.25
Maximum140
Range83
Interquartile range (IQR)20

Descriptive statistics

Standard deviation15.23324128
Coefficient of variation (CV)0.1792287866
Kurtosis3.755079698
Mean84.99327354
Median Absolute Deviation (MAD)6
Skewness1.709136591
Sum37907
Variance232.05164
MonotocityNot monotonic
2021-01-12T20:52:50.431066image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
9392
18.7%
7381
16.5%
7868
13.8%
7029
 
5.9%
8427
 
5.5%
7916
 
3.3%
14015
 
3.1%
8115
 
3.1%
10513
 
2.6%
749
 
1.8%
Other values (33)81
16.5%
(Missing)45
9.2%
ValueCountFrequency (%)
571
0.2%
592
0.4%
602
0.4%
642
0.4%
671
0.2%
ValueCountFrequency (%)
14015
3.1%
1271
 
0.2%
1212
 
0.4%
1165
 
1.0%
1092
 
0.4%

top_awarded_type
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

hide_score
Boolean

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
489 
True
 
2
ValueCountFrequency (%)
False489
99.6%
True2
 
0.4%
2021-01-12T20:52:50.500878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

name
Categorical

UNIQUE

Distinct491
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
t3_kv6b1m
 
1
t3_kv9fud
 
1
t3_kvbvv7
 
1
t3_kvl4mj
 
1
t3_ktw3mn
 
1
Other values (486)
486 

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters4419
Distinct characters37
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique491 ?
Unique (%)100.0%

Sample

1st rowt3_kvh1is
2nd rowt3_kvbi43
3rd rowt3_kvhyq3
4th rowt3_kvfouq
5th rowt3_kv8utu
ValueCountFrequency (%)
t3_kv6b1m1
 
0.2%
t3_kv9fud1
 
0.2%
t3_kvbvv71
 
0.2%
t3_kvl4mj1
 
0.2%
t3_ktw3mn1
 
0.2%
t3_kv8d661
 
0.2%
t3_ku4aim1
 
0.2%
t3_kvhyq31
 
0.2%
t3_kv5zwq1
 
0.2%
t3_kvbxue1
 
0.2%
Other values (481)481
98.0%
2021-01-12T20:52:50.686382image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
t3_kv6b1m1
 
0.2%
t3_kv9fud1
 
0.2%
t3_kvbvv71
 
0.2%
t3_kvl4mj1
 
0.2%
t3_ktw3mn1
 
0.2%
t3_kv8d661
 
0.2%
t3_ku4aim1
 
0.2%
t3_kvhyq31
 
0.2%
t3_kv5zwq1
 
0.2%
t3_kvbxue1
 
0.2%
Other values (481)481
98.0%

Most occurring characters

ValueCountFrequency (%)
k552
 
12.5%
t550
 
12.4%
3550
 
12.4%
_491
 
11.1%
v370
 
8.4%
u211
 
4.8%
575
 
1.7%
j67
 
1.5%
e67
 
1.5%
c64
 
1.4%
Other values (27)1422
32.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2854
64.6%
Decimal Number1074
 
24.3%
Connector Punctuation491
 
11.1%

Most frequent character per category

ValueCountFrequency (%)
k552
19.3%
t550
19.3%
v370
13.0%
u211
 
7.4%
j67
 
2.3%
e67
 
2.3%
c64
 
2.2%
q58
 
2.0%
l57
 
2.0%
b56
 
2.0%
Other values (16)802
28.1%
ValueCountFrequency (%)
3550
51.2%
575
 
7.0%
764
 
6.0%
664
 
6.0%
458
 
5.4%
958
 
5.4%
857
 
5.3%
152
 
4.8%
251
 
4.7%
045
 
4.2%
ValueCountFrequency (%)
_491
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2854
64.6%
Common1565
35.4%

Most frequent character per script

ValueCountFrequency (%)
k552
19.3%
t550
19.3%
v370
13.0%
u211
 
7.4%
j67
 
2.3%
e67
 
2.3%
c64
 
2.2%
q58
 
2.0%
l57
 
2.0%
b56
 
2.0%
Other values (16)802
28.1%
ValueCountFrequency (%)
3550
35.1%
_491
31.4%
575
 
4.8%
764
 
4.1%
664
 
4.1%
458
 
3.7%
958
 
3.7%
857
 
3.6%
152
 
3.3%
251
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII4419
100.0%

Most frequent character per block

ValueCountFrequency (%)
k552
 
12.5%
t550
 
12.4%
3550
 
12.4%
_491
 
11.1%
v370
 
8.4%
u211
 
4.8%
575
 
1.7%
j67
 
1.5%
e67
 
1.5%
c64
 
1.4%
Other values (27)1422
32.2%

quarantine
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:50.743232image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

link_flair_text_color
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
dark
491 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1964
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowdark
2nd rowdark
3rd rowdark
4th rowdark
5th rowdark
ValueCountFrequency (%)
dark491
100.0%
2021-01-12T20:52:50.881860image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:50.937705image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
dark491
100.0%

Most occurring characters

ValueCountFrequency (%)
d491
25.0%
a491
25.0%
r491
25.0%
k491
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1964
100.0%

Most frequent character per category

ValueCountFrequency (%)
d491
25.0%
a491
25.0%
r491
25.0%
k491
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1964
100.0%

Most frequent character per script

ValueCountFrequency (%)
d491
25.0%
a491
25.0%
r491
25.0%
k491
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1964
100.0%

Most frequent character per block

ValueCountFrequency (%)
d491
25.0%
a491
25.0%
r491
25.0%
k491
25.0%

upvote_ratio
Real number (ℝ≥0)

Distinct53
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6709164969
Minimum0.37
Maximum0.9
Zeros0
Zeros (%)0.0%
Memory size3.8 KiB
2021-01-12T20:52:51.001535image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.37
5-th percentile0.44
Q10.59
median0.69
Q30.765
95-th percentile0.84
Maximum0.9
Range0.53
Interquartile range (IQR)0.175

Descriptive statistics

Standard deviation0.1223701943
Coefficient of variation (CV)0.1823925851
Kurtosis-0.5238523472
Mean0.6709164969
Median Absolute Deviation (MAD)0.09
Skewness-0.5441871033
Sum329.42
Variance0.01497446444
MonotocityNot monotonic
2021-01-12T20:52:51.122216image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.825
 
5.1%
0.7620
 
4.1%
0.7220
 
4.1%
0.7319
 
3.9%
0.717
 
3.5%
0.6716
 
3.3%
0.7116
 
3.3%
0.6615
 
3.1%
0.6315
 
3.1%
0.7815
 
3.1%
Other values (43)313
63.7%
ValueCountFrequency (%)
0.373
0.6%
0.382
0.4%
0.393
0.6%
0.42
0.4%
0.411
 
0.2%
ValueCountFrequency (%)
0.91
 
0.2%
0.883
 
0.6%
0.872
 
0.4%
0.862
 
0.4%
0.859
1.8%
Distinct1
Distinct (%)0.3%
Missing203
Missing (%)41.3%
Memory size3.8 KiB
288 

Length

Max length3
Median length0
Mean length1.240325866
Min length0

Characters and Unicode

Total characters609
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd rownan
4th rownan
5th row
ValueCountFrequency (%)
288
58.7%
(Missing)203
41.3%
2021-01-12T20:52:51.322680image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:51.386482image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
nan203
100.0%

Most occurring characters

ValueCountFrequency (%)
n406
66.7%
a203
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter609
100.0%

Most frequent character per category

ValueCountFrequency (%)
n406
66.7%
a203
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin609
100.0%

Most frequent character per script

ValueCountFrequency (%)
n406
66.7%
a203
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII609
100.0%

Most frequent character per block

ValueCountFrequency (%)
n406
66.7%
a203
33.3%

subreddit_type
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
public
491 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters2946
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowpublic
2nd rowpublic
3rd rowpublic
4th rowpublic
5th rowpublic
ValueCountFrequency (%)
public491
100.0%
2021-01-12T20:52:51.526135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:51.580984image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
public491
100.0%

Most occurring characters

ValueCountFrequency (%)
p491
16.7%
u491
16.7%
b491
16.7%
l491
16.7%
i491
16.7%
c491
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2946
100.0%

Most frequent character per category

ValueCountFrequency (%)
p491
16.7%
u491
16.7%
b491
16.7%
l491
16.7%
i491
16.7%
c491
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin2946
100.0%

Most frequent character per script

ValueCountFrequency (%)
p491
16.7%
u491
16.7%
b491
16.7%
l491
16.7%
i491
16.7%
c491
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII2946
100.0%

Most frequent character per block

ValueCountFrequency (%)
p491
16.7%
u491
16.7%
b491
16.7%
l491
16.7%
i491
16.7%
c491
16.7%

ups
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct276
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean481.5478615
Minimum0
Maximum20080
Zeros68
Zeros (%)13.8%
Memory size3.8 KiB
2021-01-12T20:52:51.646813image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median73
Q3345.5
95-th percentile2403.5
Maximum20080
Range20080
Interquartile range (IQR)325.5

Descriptive statistics

Standard deviation1351.010137
Coefficient of variation (CV)2.80555734
Kurtosis97.84642331
Mean481.5478615
Median Absolute Deviation (MAD)71
Skewness8.151148573
Sum236440
Variance1825228.391
MonotocityNot monotonic
2021-01-12T20:52:51.757516image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
068
 
13.8%
287
 
1.4%
526
 
1.2%
226
 
1.2%
166
 
1.2%
136
 
1.2%
515
 
1.0%
385
 
1.0%
355
 
1.0%
205
 
1.0%
Other values (266)372
75.8%
ValueCountFrequency (%)
068
13.8%
11
 
0.2%
23
 
0.6%
44
 
0.8%
51
 
0.2%
ValueCountFrequency (%)
200801
0.2%
96541
0.2%
76801
0.2%
65761
0.2%
65261
0.2%

total_awards_received
Real number (ℝ≥0)

ZEROS

Distinct19
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.116089613
Minimum0
Maximum27
Zeros354
Zeros (%)72.1%
Memory size3.8 KiB
2021-01-12T20:52:51.864231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum27
Range27
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.266522488
Coefficient of variation (CV)2.926756463
Kurtosis27.46586234
Mean1.116089613
Median Absolute Deviation (MAD)0
Skewness4.885944992
Sum548
Variance10.67016917
MonotocityNot monotonic
2021-01-12T20:52:51.953992image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0354
72.1%
151
 
10.4%
230
 
6.1%
318
 
3.7%
47
 
1.4%
66
 
1.2%
55
 
1.0%
103
 
0.6%
242
 
0.4%
82
 
0.4%
Other values (9)13
 
2.6%
ValueCountFrequency (%)
0354
72.1%
151
 
10.4%
230
 
6.1%
318
 
3.7%
47
 
1.4%
ValueCountFrequency (%)
271
0.2%
242
0.4%
231
0.2%
192
0.4%
171
0.2%

media_embed
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size4.0 KiB

thumbnail_width
Categorical

MISSING

Distinct2
Distinct (%)0.4%
Missing45
Missing (%)9.2%
Memory size3.8 KiB
140
445 
70
 
1

Length

Max length5
Median length5
Mean length4.814663951
Min length3

Characters and Unicode

Total characters2364
Distinct characters7
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row140.0
2nd row140.0
3rd row140.0
4th rownan
5th row140.0
ValueCountFrequency (%)
140445
90.6%
701
 
0.2%
(Missing)45
 
9.2%
2021-01-12T20:52:52.136510image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:52.202327image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
140.0445
90.6%
nan45
 
9.2%
70.01
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0892
37.7%
.446
18.9%
1445
18.8%
4445
18.8%
n90
 
3.8%
a45
 
1.9%
71
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1783
75.4%
Other Punctuation446
 
18.9%
Lowercase Letter135
 
5.7%

Most frequent character per category

ValueCountFrequency (%)
0892
50.0%
1445
25.0%
4445
25.0%
71
 
0.1%
ValueCountFrequency (%)
n90
66.7%
a45
33.3%
ValueCountFrequency (%)
.446
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2229
94.3%
Latin135
 
5.7%

Most frequent character per script

ValueCountFrequency (%)
0892
40.0%
.446
20.0%
1445
20.0%
4445
20.0%
71
 
< 0.1%
ValueCountFrequency (%)
n90
66.7%
a45
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII2364
100.0%

Most frequent character per block

ValueCountFrequency (%)
0892
37.7%
.446
18.9%
1445
18.8%
4445
18.8%
n90
 
3.8%
a45
 
1.9%
71
 
< 0.1%

author_flair_template_id
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.9%
Missing440
Missing (%)89.6%
Memory size3.8 KiB
421b644c-8b38-11e1-bc5f-12313d18ad57
49 
6f4730d6-8b38-11e1-b67a-12313d096aae
 
1
7baa8bac-9592-11e1-a881-12313b088941
 
1

Length

Max length36
Median length3
Mean length6.427698574
Min length3

Characters and Unicode

Total characters3156
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)3.9%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan
ValueCountFrequency (%)
421b644c-8b38-11e1-bc5f-12313d18ad5749
 
10.0%
6f4730d6-8b38-11e1-b67a-12313d096aae1
 
0.2%
7baa8bac-9592-11e1-a881-12313b0889411
 
0.2%
(Missing)440
89.6%
2021-01-12T20:52:52.366887image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:52.426729image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
nan440
89.6%
421b644c-8b38-11e1-bc5f-12313d18ad5749
 
10.0%
6f4730d6-8b38-11e1-b67a-12313d096aae1
 
0.2%
7baa8bac-9592-11e1-a881-12313b0889411
 
0.2%

Most occurring characters

ValueCountFrequency (%)
n880
27.9%
a496
15.7%
1355
11.2%
-204
 
6.5%
8154
 
4.9%
3153
 
4.8%
b152
 
4.8%
4149
 
4.7%
2101
 
3.2%
d100
 
3.2%
Other values (8)412
13.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1829
58.0%
Decimal Number1123
35.6%
Dash Punctuation204
 
6.5%

Most frequent character per category

ValueCountFrequency (%)
1355
31.6%
8154
13.7%
3153
13.6%
4149
13.3%
2101
 
9.0%
599
 
8.8%
653
 
4.7%
752
 
4.6%
94
 
0.4%
03
 
0.3%
ValueCountFrequency (%)
n880
48.1%
a496
27.1%
b152
 
8.3%
d100
 
5.5%
c99
 
5.4%
e52
 
2.8%
f50
 
2.7%
ValueCountFrequency (%)
-204
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1829
58.0%
Common1327
42.0%

Most frequent character per script

ValueCountFrequency (%)
1355
26.8%
-204
15.4%
8154
11.6%
3153
11.5%
4149
11.2%
2101
 
7.6%
599
 
7.5%
653
 
4.0%
752
 
3.9%
94
 
0.3%
ValueCountFrequency (%)
n880
48.1%
a496
27.1%
b152
 
8.3%
d100
 
5.5%
c99
 
5.4%
e52
 
2.8%
f50
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII3156
100.0%

Most frequent character per block

ValueCountFrequency (%)
n880
27.9%
a496
15.7%
1355
11.2%
-204
 
6.5%
8154
 
4.9%
3153
 
4.8%
b152
 
4.8%
4149
 
4.7%
2101
 
3.2%
d100
 
3.2%
Other values (8)412
13.1%

is_original_content
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:52.481585image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

user_reports
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size4.0 KiB

secure_media
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing488
Missing (%)99.4%
Memory size4.0 KiB
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
485 
True
 
6
ValueCountFrequency (%)
False485
98.8%
True6
 
1.2%
2021-01-12T20:52:52.510499image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

is_meta
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:52.547404image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

category
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

secure_media_embed
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size4.0 KiB

link_flair_text
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)0.6%
Missing8
Missing (%)1.6%
Memory size3.8 KiB
Flaired Users Only
465 
Satire - Flaired Users Only
 
17
Misleading Title
 
1

Length

Max length27
Median length18
Mean length18.06313646
Min length3

Characters and Unicode

Total characters8869
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowFlaired Users Only
2nd rowFlaired Users Only
3rd rowFlaired Users Only
4th rowFlaired Users Only
5th rowFlaired Users Only
ValueCountFrequency (%)
Flaired Users Only465
94.7%
Satire - Flaired Users Only17
 
3.5%
Misleading Title1
 
0.2%
(Missing)8
 
1.6%
2021-01-12T20:52:52.695009image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:52.896500image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
users482
32.3%
only482
32.3%
flaired482
32.3%
satire17
 
1.1%
17
 
1.1%
nan8
 
0.5%
misleading1
 
0.1%
title1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
999
11.3%
e983
11.1%
r981
11.1%
l966
10.9%
s965
10.9%
a508
 
5.7%
i502
 
5.7%
n499
 
5.6%
d483
 
5.4%
F482
 
5.4%
Other values (9)1501
16.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6388
72.0%
Uppercase Letter1465
 
16.5%
Space Separator999
 
11.3%
Dash Punctuation17
 
0.2%

Most frequent character per category

ValueCountFrequency (%)
e983
15.4%
r981
15.4%
l966
15.1%
s965
15.1%
a508
8.0%
i502
7.9%
n499
7.8%
d483
7.6%
y482
7.5%
t18
 
0.3%
ValueCountFrequency (%)
F482
32.9%
U482
32.9%
O482
32.9%
S17
 
1.2%
M1
 
0.1%
T1
 
0.1%
ValueCountFrequency (%)
999
100.0%
ValueCountFrequency (%)
-17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7853
88.5%
Common1016
 
11.5%

Most frequent character per script

ValueCountFrequency (%)
e983
12.5%
r981
12.5%
l966
12.3%
s965
12.3%
a508
6.5%
i502
6.4%
n499
6.4%
d483
6.2%
F482
6.1%
U482
6.1%
Other values (7)1002
12.8%
ValueCountFrequency (%)
999
98.3%
-17
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII8869
100.0%

Most frequent character per block

ValueCountFrequency (%)
999
11.3%
e983
11.1%
r981
11.1%
l966
10.9%
s965
10.9%
a508
 
5.7%
i502
 
5.7%
n499
 
5.6%
d483
 
5.4%
F482
 
5.4%
Other values (9)1501
16.9%

can_mod_post
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:52.948361image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

score
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct276
Distinct (%)56.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean481.5478615
Minimum0
Maximum20080
Zeros68
Zeros (%)13.8%
Memory size3.8 KiB
2021-01-12T20:52:53.013217image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median73
Q3345.5
95-th percentile2403.5
Maximum20080
Range20080
Interquartile range (IQR)325.5

Descriptive statistics

Standard deviation1351.010137
Coefficient of variation (CV)2.80555734
Kurtosis97.84642331
Mean481.5478615
Median Absolute Deviation (MAD)71
Skewness8.151148573
Sum236440
Variance1825228.391
MonotocityNot monotonic
2021-01-12T20:52:53.123923image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
068
 
13.8%
287
 
1.4%
526
 
1.2%
226
 
1.2%
166
 
1.2%
136
 
1.2%
515
 
1.0%
385
 
1.0%
355
 
1.0%
205
 
1.0%
Other values (266)372
75.8%
ValueCountFrequency (%)
068
13.8%
11
 
0.2%
23
 
0.6%
44
 
0.8%
51
 
0.2%
ValueCountFrequency (%)
200801
0.2%
96541
0.2%
76801
0.2%
65761
0.2%
65261
0.2%

approved_by
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size491.0 B
True
270 
False
221 
ValueCountFrequency (%)
True270
55.0%
False221
45.0%
2021-01-12T20:52:53.209696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

thumbnail
Categorical

HIGH CARDINALITY

Distinct434
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
default
45 
https://b.thumbs.redditmedia.com/_W8OdZ6QcBecS8vDQjlm9Lq0S-UbdfjtwetJXNbOIks.jpg
 
4
https://b.thumbs.redditmedia.com/i0ZoMQTie2jquTWb_t28LL13eEDih8H6SiTj1AiRmCE.jpg
 
2
https://b.thumbs.redditmedia.com/zxOEJp5r_DLc8RcpZLA1BV7hKKp1H-SpC5XDdTkhyKw.jpg
 
2
https://b.thumbs.redditmedia.com/MPaBKzwVWbNUhj5OoVYoRUhP5g_57FJwkX8FMpqAFdI.jpg
 
2
Other values (429)
436 

Length

Max length80
Median length80
Mean length73.3095723
Min length7

Characters and Unicode

Total characters35995
Distinct characters67
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique422 ?
Unique (%)85.9%

Sample

1st rowhttps://b.thumbs.redditmedia.com/KouUuQMiFYEXbo5UbYqcM0GTCRoKFKVa1ENvS08IQ6k.jpg
2nd rowhttps://b.thumbs.redditmedia.com/as1z44nQd08pAyALM9a7RJ4Woz4kwW3JSjlEnIs2lFE.jpg
3rd rowhttps://a.thumbs.redditmedia.com/3W30nlYwDUO5EksP8B1aYhW2_O5SCPdi9RSyvAYXI48.jpg
4th rowdefault
5th rowhttps://b.thumbs.redditmedia.com/9LZwi_df_op0UICOPRpzthVs76DZ4aTSMKDLVN6-mig.jpg
ValueCountFrequency (%)
default45
 
9.2%
https://b.thumbs.redditmedia.com/_W8OdZ6QcBecS8vDQjlm9Lq0S-UbdfjtwetJXNbOIks.jpg4
 
0.8%
https://b.thumbs.redditmedia.com/i0ZoMQTie2jquTWb_t28LL13eEDih8H6SiTj1AiRmCE.jpg2
 
0.4%
https://b.thumbs.redditmedia.com/zxOEJp5r_DLc8RcpZLA1BV7hKKp1H-SpC5XDdTkhyKw.jpg2
 
0.4%
https://b.thumbs.redditmedia.com/MPaBKzwVWbNUhj5OoVYoRUhP5g_57FJwkX8FMpqAFdI.jpg2
 
0.4%
https://a.thumbs.redditmedia.com/6pTnhoDSi3u9iubBvKOngUY9XgtI8rV-2cAiinozB58.jpg2
 
0.4%
https://b.thumbs.redditmedia.com/-iwUcnQZ7XA3XVmUGtgKJCkp8ORVtZZHY1Q8GU9X6uY.jpg2
 
0.4%
https://a.thumbs.redditmedia.com/H7QRLlCjRxMCBZYEQA6rCokzZu9C_zGlCBh_RV49jR4.jpg2
 
0.4%
https://b.thumbs.redditmedia.com/tD7M4CrXchbIeED68pncrEZwHYvs8FJqQHP7iQWpORQ.jpg2
 
0.4%
https://b.thumbs.redditmedia.com/zpvaUn00zdlGn3WWRiqzua6ZbfvW5fI3huaZ56P2Hhw.jpg2
 
0.4%
Other values (424)426
86.8%
2021-01-12T20:52:53.405170image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
default45
 
9.2%
https://b.thumbs.redditmedia.com/_w8odz6qcbecs8vdqjlm9lq0s-ubdfjtwetjxnboiks.jpg4
 
0.8%
https://b.thumbs.redditmedia.com/i0zomqtie2jqutwb_t28ll13eedih8h6sitj1airmce.jpg2
 
0.4%
https://a.thumbs.redditmedia.com/6ptnhodsi3u9iubbvkonguy9xgti8rv-2caiinozb58.jpg2
 
0.4%
https://b.thumbs.redditmedia.com/zpvaun00zdlgn3wwriqzua6zbfvw5fi3huaz56p2hhw.jpg2
 
0.4%
https://b.thumbs.redditmedia.com/td7m4crxchbieed68pncrezwhyvs8fjqqhp7iqwporq.jpg2
 
0.4%
https://b.thumbs.redditmedia.com/mpabkzwvwbnuhj5oovyoruhp5g_57fjwkx8fmpqafdi.jpg2
 
0.4%
https://b.thumbs.redditmedia.com/favpc7rkcnk2kmxrbd2qmc9qhpwozlsnqg2unaz0ofu.jpg2
 
0.4%
https://b.thumbs.redditmedia.com/mux120owk9ylbebtkle8qipysepwnscpe26hcnvncsm.jpg2
 
0.4%
https://a.thumbs.redditmedia.com/h7qrllcjrxmcbzyeqa6rcokzzu9c_zglcbh_rv49jr4.jpg2
 
0.4%
Other values (424)426
86.8%

Most occurring characters

ValueCountFrequency (%)
t2094
 
5.8%
.1784
 
5.0%
d1671
 
4.6%
m1632
 
4.5%
/1338
 
3.7%
e1239
 
3.4%
s1215
 
3.4%
i1215
 
3.4%
p1204
 
3.3%
h1193
 
3.3%
Other values (57)21410
59.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter21159
58.8%
Uppercase Letter7770
 
21.6%
Other Punctuation3568
 
9.9%
Decimal Number2927
 
8.1%
Connector Punctuation293
 
0.8%
Dash Punctuation278
 
0.8%

Most frequent character per category

ValueCountFrequency (%)
t2094
 
9.9%
d1671
 
7.9%
m1632
 
7.7%
e1239
 
5.9%
s1215
 
5.7%
i1215
 
5.7%
p1204
 
5.7%
h1193
 
5.6%
b1120
 
5.3%
a871
 
4.1%
Other values (16)7705
36.4%
ValueCountFrequency (%)
Y332
 
4.3%
R324
 
4.2%
A322
 
4.1%
I316
 
4.1%
Q313
 
4.0%
V312
 
4.0%
U311
 
4.0%
F310
 
4.0%
W308
 
4.0%
T306
 
3.9%
Other values (16)4616
59.4%
ValueCountFrequency (%)
8344
11.8%
7321
11.0%
0319
10.9%
4310
10.6%
1300
10.2%
9279
9.5%
5276
9.4%
6273
9.3%
3267
9.1%
2238
8.1%
ValueCountFrequency (%)
.1784
50.0%
/1338
37.5%
:446
 
12.5%
ValueCountFrequency (%)
_293
100.0%
ValueCountFrequency (%)
-278
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin28929
80.4%
Common7066
 
19.6%

Most frequent character per script

ValueCountFrequency (%)
t2094
 
7.2%
d1671
 
5.8%
m1632
 
5.6%
e1239
 
4.3%
s1215
 
4.2%
i1215
 
4.2%
p1204
 
4.2%
h1193
 
4.1%
b1120
 
3.9%
a871
 
3.0%
Other values (42)15475
53.5%
ValueCountFrequency (%)
.1784
25.2%
/1338
18.9%
:446
 
6.3%
8344
 
4.9%
7321
 
4.5%
0319
 
4.5%
4310
 
4.4%
1300
 
4.2%
_293
 
4.1%
9279
 
3.9%
Other values (5)1332
18.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII35995
100.0%

Most frequent character per block

ValueCountFrequency (%)
t2094
 
5.8%
.1784
 
5.0%
d1671
 
4.6%
m1632
 
4.5%
/1338
 
3.7%
e1239
 
3.4%
s1215
 
3.4%
i1215
 
3.4%
p1204
 
3.3%
h1193
 
3.3%
Other values (57)21410
59.5%

edited
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:53.468013image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

author_flair_css_class
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)9.3%
Missing437
Missing (%)89.0%
Memory size3.8 KiB
Conservative
49 
 
2
GREENBOLD
 
1
Libertarian Conservative
 
1
Constitutional Conservative
 
1

Length

Max length27
Median length3
Mean length3.989816701
Min length0

Characters and Unicode

Total characters1959
Distinct characters22
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)5.6%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan
ValueCountFrequency (%)
Conservative49
 
10.0%
2
 
0.4%
GREENBOLD1
 
0.2%
Libertarian Conservative1
 
0.2%
Constitutional Conservative1
 
0.2%
(Missing)437
89.0%
2021-01-12T20:52:53.626578image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:53.686414image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
nan437
89.0%
conservative51
 
10.4%
constitutional1
 
0.2%
libertarian1
 
0.2%
greenbold1
 
0.2%

Most occurring characters

ValueCountFrequency (%)
n928
47.4%
a491
25.1%
e103
 
5.3%
v102
 
5.2%
t55
 
2.8%
i55
 
2.8%
o53
 
2.7%
r53
 
2.7%
C52
 
2.7%
s52
 
2.7%
Other values (12)15
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1895
96.7%
Uppercase Letter62
 
3.2%
Space Separator2
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
n928
49.0%
a491
25.9%
e103
 
5.4%
v102
 
5.4%
t55
 
2.9%
i55
 
2.9%
o53
 
2.8%
r53
 
2.8%
s52
 
2.7%
b1
 
0.1%
Other values (2)2
 
0.1%
ValueCountFrequency (%)
C52
83.9%
L2
 
3.2%
E2
 
3.2%
G1
 
1.6%
R1
 
1.6%
N1
 
1.6%
B1
 
1.6%
O1
 
1.6%
D1
 
1.6%
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1957
99.9%
Common2
 
0.1%

Most frequent character per script

ValueCountFrequency (%)
n928
47.4%
a491
25.1%
e103
 
5.3%
v102
 
5.2%
t55
 
2.8%
i55
 
2.8%
o53
 
2.7%
r53
 
2.7%
C52
 
2.7%
s52
 
2.7%
Other values (11)13
 
0.7%
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1959
100.0%

Most frequent character per block

ValueCountFrequency (%)
n928
47.4%
a491
25.1%
e103
 
5.3%
v102
 
5.2%
t55
 
2.8%
i55
 
2.8%
o53
 
2.7%
r53
 
2.7%
C52
 
2.7%
s52
 
2.7%
Other values (12)15
 
0.8%

author_flair_richtext
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size4.0 KiB

gildings
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size4.0 KiB

post_hint
Categorical

MISSING

Distinct3
Distinct (%)0.7%
Missing47
Missing (%)9.6%
Memory size3.8 KiB
link
436 
image
 
5
rich:video
 
3

Length

Max length10
Median length4
Mean length3.951120163
Min length3

Characters and Unicode

Total characters1940
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowlink
2nd rowlink
3rd rowimage
4th rownan
5th rowlink
ValueCountFrequency (%)
link436
88.8%
image5
 
1.0%
rich:video3
 
0.6%
(Missing)47
 
9.6%
2021-01-12T20:52:53.883889image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:53.949711image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
link436
88.8%
nan47
 
9.6%
image5
 
1.0%
rich:video3
 
0.6%

Most occurring characters

ValueCountFrequency (%)
n530
27.3%
i447
23.0%
l436
22.5%
k436
22.5%
a52
 
2.7%
e8
 
0.4%
m5
 
0.3%
g5
 
0.3%
r3
 
0.2%
c3
 
0.2%
Other values (5)15
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1937
99.8%
Other Punctuation3
 
0.2%

Most frequent character per category

ValueCountFrequency (%)
n530
27.4%
i447
23.1%
l436
22.5%
k436
22.5%
a52
 
2.7%
e8
 
0.4%
m5
 
0.3%
g5
 
0.3%
r3
 
0.2%
c3
 
0.2%
Other values (4)12
 
0.6%
ValueCountFrequency (%)
:3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1937
99.8%
Common3
 
0.2%

Most frequent character per script

ValueCountFrequency (%)
n530
27.4%
i447
23.1%
l436
22.5%
k436
22.5%
a52
 
2.7%
e8
 
0.4%
m5
 
0.3%
g5
 
0.3%
r3
 
0.2%
c3
 
0.2%
Other values (4)12
 
0.6%
ValueCountFrequency (%)
:3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1940
100.0%

Most frequent character per block

ValueCountFrequency (%)
n530
27.3%
i447
23.0%
l436
22.5%
k436
22.5%
a52
 
2.7%
e8
 
0.4%
m5
 
0.3%
g5
 
0.3%
r3
 
0.2%
c3
 
0.2%
Other values (5)15
 
0.8%

content_categories
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

is_self
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:53.997620image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

mod_note
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

created
Real number (ℝ≥0)

HIGH CORRELATION

Distinct490
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1610390927
Minimum1610226496
Maximum1610482534
Zeros0
Zeros (%)0.0%
Memory size3.8 KiB
2021-01-12T20:52:54.057460image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1610226496
5-th percentile1610276492
Q11610349375
median1610411822
Q31610428838
95-th percentile1610453033
Maximum1610482534
Range256038
Interquartile range (IQR)79463

Descriptive statistics

Standard deviation54841.2184
Coefficient of variation (CV)3.405459971 × 105
Kurtosis0.2141099265
Mean1610390927
Median Absolute Deviation (MAD)25638
Skewness-1.00138612
Sum7.907019452 × 1011
Variance3007559235
MonotocityNot monotonic
2021-01-12T20:52:54.166171image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16104096192
 
0.4%
16104110201
 
0.2%
16104330741
 
0.2%
16104028111
 
0.2%
16104258641
 
0.2%
16104273451
 
0.2%
16104185911
 
0.2%
16103985951
 
0.2%
16104240791
 
0.2%
16104295641
 
0.2%
Other values (480)480
97.8%
ValueCountFrequency (%)
16102264961
0.2%
16102269371
0.2%
16102363311
0.2%
16102378581
0.2%
16102389951
0.2%
ValueCountFrequency (%)
16104825341
0.2%
16104810451
0.2%
16104756671
0.2%
16104744971
0.2%
16104715991
0.2%

link_flair_type
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
richtext
483 
text
 
8

Length

Max length8
Median length8
Mean length7.934826884
Min length4

Characters and Unicode

Total characters3896
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowrichtext
2nd rowrichtext
3rd rowrichtext
4th rowrichtext
5th rowrichtext
ValueCountFrequency (%)
richtext483
98.4%
text8
 
1.6%
2021-01-12T20:52:54.359655image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:54.426473image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
richtext483
98.4%
text8
 
1.6%

Most occurring characters

ValueCountFrequency (%)
t982
25.2%
e491
12.6%
x491
12.6%
r483
12.4%
i483
12.4%
c483
12.4%
h483
12.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3896
100.0%

Most frequent character per category

ValueCountFrequency (%)
t982
25.2%
e491
12.6%
x491
12.6%
r483
12.4%
i483
12.4%
c483
12.4%
h483
12.4%

Most occurring scripts

ValueCountFrequency (%)
Latin3896
100.0%

Most frequent character per script

ValueCountFrequency (%)
t982
25.2%
e491
12.6%
x491
12.6%
r483
12.4%
i483
12.4%
c483
12.4%
h483
12.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII3896
100.0%

Most frequent character per block

ValueCountFrequency (%)
t982
25.2%
e491
12.6%
x491
12.6%
r483
12.4%
i483
12.4%
c483
12.4%
h483
12.4%

wls
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
7
491 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters491
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7
2nd row7
3rd row7
4th row7
5th row7
ValueCountFrequency (%)
7491
100.0%
2021-01-12T20:52:54.576073image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:54.631931image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
7491
100.0%

Most occurring characters

ValueCountFrequency (%)
7491
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number491
100.0%

Most frequent character per category

ValueCountFrequency (%)
7491
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common491
100.0%

Most frequent character per script

ValueCountFrequency (%)
7491
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII491
100.0%

Most frequent character per block

ValueCountFrequency (%)
7491
100.0%

removed_by_category
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

banned_by
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

author_flair_type
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
richtext
336 
text
155 

Length

Max length8
Median length8
Mean length6.737270876
Min length4

Characters and Unicode

Total characters3308
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowrichtext
2nd rowrichtext
3rd rowtext
4th rowtext
5th rowrichtext
ValueCountFrequency (%)
richtext336
68.4%
text155
31.6%
2021-01-12T20:52:54.795486image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:54.866297image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
richtext336
68.4%
text155
31.6%

Most occurring characters

ValueCountFrequency (%)
t982
29.7%
e491
14.8%
x491
14.8%
r336
 
10.2%
i336
 
10.2%
c336
 
10.2%
h336
 
10.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3308
100.0%

Most frequent character per category

ValueCountFrequency (%)
t982
29.7%
e491
14.8%
x491
14.8%
r336
 
10.2%
i336
 
10.2%
c336
 
10.2%
h336
 
10.2%

Most occurring scripts

ValueCountFrequency (%)
Latin3308
100.0%

Most frequent character per script

ValueCountFrequency (%)
t982
29.7%
e491
14.8%
x491
14.8%
r336
 
10.2%
i336
 
10.2%
c336
 
10.2%
h336
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII3308
100.0%

Most frequent character per block

ValueCountFrequency (%)
t982
29.7%
e491
14.8%
x491
14.8%
r336
 
10.2%
i336
 
10.2%
c336
 
10.2%
h336
 
10.2%

domain
Categorical

HIGH CARDINALITY

Distinct149
Distinct (%)30.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
theepochtimes.com
39 
foxnews.com
 
28
breitbart.com
 
27
dailywire.com
 
24
dailymail.co.uk
 
19
Other values (144)
354 

Length

Max length27
Median length13
Mean length14.02443992
Min length6

Characters and Unicode

Total characters6886
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)18.3%

Sample

1st rowwashingtonexaminer.com
2nd rowtwitchy.com
3rd rowi.redd.it
4th rowtownhall.com
5th rowdigitaltrends.com
ValueCountFrequency (%)
theepochtimes.com39
 
7.9%
foxnews.com28
 
5.7%
breitbart.com27
 
5.5%
dailywire.com24
 
4.9%
dailymail.co.uk19
 
3.9%
redstate.com15
 
3.1%
wsj.com15
 
3.1%
washingtonexaminer.com12
 
2.4%
townhall.com12
 
2.4%
babylonbee.com12
 
2.4%
Other values (139)288
58.7%
2021-01-12T20:52:55.075736image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
theepochtimes.com39
 
7.9%
foxnews.com28
 
5.7%
breitbart.com27
 
5.5%
dailywire.com24
 
4.9%
dailymail.co.uk19
 
3.9%
redstate.com15
 
3.1%
wsj.com15
 
3.1%
washingtonexaminer.com12
 
2.4%
townhall.com12
 
2.4%
babylonbee.com12
 
2.4%
Other values (139)288
58.7%

Most occurring characters

ValueCountFrequency (%)
o721
 
10.5%
e677
 
9.8%
m577
 
8.4%
c577
 
8.4%
.538
 
7.8%
t470
 
6.8%
a383
 
5.6%
i376
 
5.5%
s326
 
4.7%
n309
 
4.5%
Other values (22)1932
28.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6333
92.0%
Other Punctuation538
 
7.8%
Decimal Number8
 
0.1%
Dash Punctuation7
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
o721
11.4%
e677
10.7%
m577
 
9.1%
c577
 
9.1%
t470
 
7.4%
a383
 
6.0%
i376
 
5.9%
s326
 
5.1%
n309
 
4.9%
r298
 
4.7%
Other values (16)1619
25.6%
ValueCountFrequency (%)
13
37.5%
92
25.0%
52
25.0%
31
 
12.5%
ValueCountFrequency (%)
.538
100.0%
ValueCountFrequency (%)
-7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6333
92.0%
Common553
 
8.0%

Most frequent character per script

ValueCountFrequency (%)
o721
11.4%
e677
10.7%
m577
 
9.1%
c577
 
9.1%
t470
 
7.4%
a383
 
6.0%
i376
 
5.9%
s326
 
5.1%
n309
 
4.9%
r298
 
4.7%
Other values (16)1619
25.6%
ValueCountFrequency (%)
.538
97.3%
-7
 
1.3%
13
 
0.5%
92
 
0.4%
52
 
0.4%
31
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII6886
100.0%

Most frequent character per block

ValueCountFrequency (%)
o721
 
10.5%
e677
 
9.8%
m577
 
8.4%
c577
 
8.4%
.538
 
7.8%
t470
 
6.8%
a383
 
5.6%
i376
 
5.5%
s326
 
4.7%
n309
 
4.5%
Other values (22)1932
28.1%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
396 
True
95 
ValueCountFrequency (%)
False396
80.7%
True95
 
19.3%
2021-01-12T20:52:55.141560image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

selftext_html
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

likes
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

suggested_sort
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
confidence
491 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters4910
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowconfidence
2nd rowconfidence
3rd rowconfidence
4th rowconfidence
5th rowconfidence
ValueCountFrequency (%)
confidence491
100.0%
2021-01-12T20:52:55.289166image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:55.344018image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
confidence491
100.0%

Most occurring characters

ValueCountFrequency (%)
c982
20.0%
n982
20.0%
e982
20.0%
o491
10.0%
f491
10.0%
i491
10.0%
d491
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4910
100.0%

Most frequent character per category

ValueCountFrequency (%)
c982
20.0%
n982
20.0%
e982
20.0%
o491
10.0%
f491
10.0%
i491
10.0%
d491
10.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4910
100.0%

Most frequent character per script

ValueCountFrequency (%)
c982
20.0%
n982
20.0%
e982
20.0%
o491
10.0%
f491
10.0%
i491
10.0%
d491
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4910
100.0%

Most frequent character per block

ValueCountFrequency (%)
c982
20.0%
n982
20.0%
e982
20.0%
o491
10.0%
f491
10.0%
i491
10.0%
d491
10.0%

banned_at_utc
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB
Distinct488
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
https://www.foxnews.com/politics/fbi-internal-memo-warns-of-plans-for-armed-protests-in-all-50-state-capitals-ahead-of-biden-inauguration
 
2
https://www.oann.com/joe-biden-pledges-to-defeat-the-nra/
 
2
https://thefederalist.com/2021/01/11/left-wing-terrorists-bombed-the-senate-in-1983-bill-clinton-let-them-out-of-prison-early-at-jerry-nadlers-request/
 
2
https://deadline.com/2021/01/nbc-sports-benches-nhl-analyst-mike-milbury-stanley-cup-playoffs-insulting-comments-about-women-1203020857/
 
1
https://www.supremecourt.gov/opinions/16pdf/15-1194_08l1.pdf
 
1
Other values (483)
483 
ValueCountFrequency (%)
https://www.foxnews.com/politics/fbi-internal-memo-warns-of-plans-for-armed-protests-in-all-50-state-capitals-ahead-of-biden-inauguration2
 
0.4%
https://www.oann.com/joe-biden-pledges-to-defeat-the-nra/2
 
0.4%
https://thefederalist.com/2021/01/11/left-wing-terrorists-bombed-the-senate-in-1983-bill-clinton-let-them-out-of-prison-early-at-jerry-nadlers-request/2
 
0.4%
https://deadline.com/2021/01/nbc-sports-benches-nhl-analyst-mike-milbury-stanley-cup-playoffs-insulting-comments-about-women-1203020857/1
 
0.2%
https://www.supremecourt.gov/opinions/16pdf/15-1194_08l1.pdf1
 
0.2%
https://www.theepochtimes.com/missouri-court-rejects-st-louis-prosecutors-appeal-in-mccloskey-case_3650523.html1
 
0.2%
https://globalnews.ca/news/7567802/trump-resign-pressure-supporters/1
 
0.2%
https://www.newsmax.com/us/d-c-trump-biden-capitol/2021/01/11/id/1005169/1
 
0.2%
https://www.newsmax.com/politics/cancel-culture-stripe-payments-online/2021/01/10/id/1005008/1
 
0.2%
https://www.dailymail.co.uk/news/article-9134819/Group-demands-ethics-inquiry-GOPs-Mo-Brooks-speech-rally-prompted-Capitol-siege.html1
 
0.2%
Other values (478)478
97.4%
ValueCountFrequency (%)
https482
98.2%
http9
 
1.8%
ValueCountFrequency (%)
www.theepochtimes.com39
 
7.9%
www.foxnews.com28
 
5.7%
www.breitbart.com27
 
5.5%
www.dailywire.com24
 
4.9%
www.dailymail.co.uk19
 
3.9%
redstate.com15
 
3.1%
www.wsj.com15
 
3.1%
townhall.com12
 
2.4%
babylonbee.com12
 
2.4%
www.washingtonexaminer.com12
 
2.4%
Other values (140)288
58.7%
ValueCountFrequency (%)
/articles/the-progressive-purge-begins-116103193764
 
0.8%
/watch3
 
0.6%
/2021/01/10/twitter-hasnt-suspended-these-accounts-or-tweets-that-openly-incite-violence/2
 
0.4%
/republican-blocks-house-from-bringing-up-25th-amendment-bill_3652031.html2
 
0.4%
/twitter-shares-drop-by-12-percent-after-company-banned-trump_3652172.html2
 
0.4%
/russian-dissident-alexei-navalny-rebukes-twitter-for-censorship-of-trump_3651945.html2
 
0.4%
/aclu-warns-of-unchecked-power-after-facebook-twitter-suspend-trump_3650715.html2
 
0.4%
/potus-cut-off-supporters-even-email-company-suspends-trumps-service/2
 
0.4%
/joe-biden-pledges-to-defeat-the-nra/2
 
0.4%
/news/articles/2021-01-11/merkel-sees-closing-trump-s-social-media-accounts-problematic2
 
0.4%
Other values (462)468
95.3%
ValueCountFrequency (%)
440
89.6%
utm_source=news&amp;utm_medium=reddit&amp;utm_campaign=breaking-2021-01-11-22
 
0.4%
mod=hp_opin_pos_1&amp;fbclid=IwAR2Wbd6TXRo02cmyHxiCTeVp0S9qSsStU04q5M0bSnkueyYBWmj318dfs-k1
 
0.2%
v=pOmXiapfCs81
 
0.2%
utm_source=feedburner&amp;utm_medium=feed&amp;utm_campaign=Feed%3A+breitbart+%28Breitbart+News%291
 
0.2%
fbclid=IwAR2-dHT4Ls_3JJXbUGiOhckNNoc1U2XiUcKYXE-u0djMDB0MCUQ4W0uFIEo1
 
0.2%
cmpid=socialflow-twitter-business&amp;utm_source=twitter&amp;utm_medium=social&amp;utm_content=business&amp;utm_campaign=socialflow-organic1
 
0.2%
utm_source=justthenews.com&amp;amp;utm_medium=feed&amp;amp;utm_campaign=external-news-aggregators1
 
0.2%
sh=2d3f1b302d461
 
0.2%
sh=5451ab5cf6991
 
0.2%
Other values (41)41
 
8.4%
ValueCountFrequency (%)
487
99.2%
&amp;_intcmp=hp1bt3,hp1bt1
 
0.2%
processed1
 
0.2%
038;utm_medium=conservativetribune&amp;#038;utm_campaign=parler1
 
0.2%
comment1
 
0.2%

view_count
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

archived
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:55.372944image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

no_follow
Boolean

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
456 
True
 
35
ValueCountFrequency (%)
False456
92.9%
True35
 
7.1%
2021-01-12T20:52:55.400867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

is_crosspostable
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:55.437768image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

pinned
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:55.464696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

over_18
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:55.491624image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

preview
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing47
Missing (%)9.6%
Memory size4.0 KiB

all_awardings
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size4.0 KiB

awarders
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size4.0 KiB

media_only
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:55.518554image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

can_gild
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:55.548472image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

spoiler
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:55.575400image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

locked
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:55.603325image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

author_flair_text
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct55
Distinct (%)16.2%
Missing152
Missing (%)31.0%
Memory size3.8 KiB
Conservative
183 
Churchillian
 
15
MAGA
 
13
Moderate Conservative
 
12
Illegitimi non carborundum
 
11
Other values (50)
105 

Length

Max length29
Median length12
Mean length10.73727088
Min length0

Characters and Unicode

Total characters5272
Distinct characters74
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)9.1%

Sample

1st rowConservative
2nd rowConservative
3rd rownan
4th rownan
5th rowConservative
ValueCountFrequency (%)
Conservative183
37.3%
Churchillian15
 
3.1%
MAGA13
 
2.6%
Moderate Conservative12
 
2.4%
Illegitimi non carborundum11
 
2.2%
Milton Friedman11
 
2.2%
Anti-Marxist10
 
2.0%
Conservative Millennial7
 
1.4%
Constitutional Conservative6
 
1.2%
Washington Times, Official4
 
0.8%
Other values (45)67
 
13.6%
(Missing)152
31.0%
2021-01-12T20:52:55.803790image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
conservative241
38.6%
nan152
24.4%
churchillian15
 
2.4%
maga13
 
2.1%
moderate12
 
1.9%
illegitimi11
 
1.8%
carborundum11
 
1.8%
milton11
 
1.8%
non11
 
1.8%
friedman11
 
1.8%
Other values (75)136
21.8%

Most occurring characters

ValueCountFrequency (%)
n702
13.3%
e593
11.2%
a540
10.2%
v487
9.2%
i447
8.5%
t360
 
6.8%
r349
 
6.6%
o331
 
6.3%
s290
 
5.5%
C273
 
5.2%
Other values (64)900
17.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4594
87.1%
Uppercase Letter516
 
9.8%
Space Separator137
 
2.6%
Dash Punctuation11
 
0.2%
Other Symbol6
 
0.1%
Other Punctuation5
 
0.1%
Decimal Number3
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
n702
15.3%
e593
12.9%
a540
11.8%
v487
10.6%
i447
9.7%
t360
7.8%
r349
7.6%
o331
7.2%
s290
6.3%
l138
 
3.0%
Other values (26)357
7.8%
ValueCountFrequency (%)
C273
52.9%
M58
 
11.2%
A46
 
8.9%
F21
 
4.1%
G16
 
3.1%
I16
 
3.1%
R11
 
2.1%
L10
 
1.9%
T9
 
1.7%
S8
 
1.6%
Other values (20)48
 
9.3%
ValueCountFrequency (%)
21
33.3%
11
33.3%
01
33.3%
ValueCountFrequency (%)
,4
80.0%
'1
 
20.0%
ValueCountFrequency (%)
-11
100.0%
ValueCountFrequency (%)
137
100.0%
ValueCountFrequency (%)
💩6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5085
96.5%
Common162
 
3.1%
Cyrillic16
 
0.3%
Greek9
 
0.2%

Most frequent character per script

ValueCountFrequency (%)
n702
13.8%
e593
11.7%
a540
10.6%
v487
9.6%
i447
8.8%
t360
7.1%
r349
6.9%
o331
6.5%
s290
5.7%
C273
 
5.4%
Other values (34)713
14.0%
ValueCountFrequency (%)
т2
12.5%
и2
12.5%
П1
 
6.2%
у1
 
6.2%
н1
 
6.2%
м1
 
6.2%
о1
 
6.2%
й1
 
6.2%
п1
 
6.2%
р1
 
6.2%
Other values (4)4
25.0%
ValueCountFrequency (%)
137
84.6%
-11
 
6.8%
💩6
 
3.7%
,4
 
2.5%
21
 
0.6%
'1
 
0.6%
11
 
0.6%
01
 
0.6%
ValueCountFrequency (%)
Λ2
22.2%
Μ1
11.1%
Ο1
11.1%
Ω1
11.1%
Ν1
11.1%
Α1
11.1%
Β1
11.1%
Ε1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII5241
99.4%
Cyrillic16
 
0.3%
None15
 
0.3%

Most frequent character per block

ValueCountFrequency (%)
n702
13.4%
e593
11.3%
a540
10.3%
v487
9.3%
i447
8.5%
t360
6.9%
r349
6.7%
o331
 
6.3%
s290
 
5.5%
C273
 
5.2%
Other values (41)869
16.6%
ValueCountFrequency (%)
💩6
40.0%
Λ2
 
13.3%
Μ1
 
6.7%
Ο1
 
6.7%
Ω1
 
6.7%
Ν1
 
6.7%
Α1
 
6.7%
Β1
 
6.7%
Ε1
 
6.7%
ValueCountFrequency (%)
т2
12.5%
и2
12.5%
П1
 
6.2%
у1
 
6.2%
н1
 
6.2%
м1
 
6.2%
о1
 
6.2%
й1
 
6.2%
п1
 
6.2%
р1
 
6.2%
Other values (4)4
25.0%

treatment_tags
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size4.0 KiB

visited
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:55.877625image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

removed_by
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

num_reports
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

distinguished
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

subreddit_id
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
t5_2qh6p
491 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters3928
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowt5_2qh6p
2nd rowt5_2qh6p
3rd rowt5_2qh6p
4th rowt5_2qh6p
5th rowt5_2qh6p
ValueCountFrequency (%)
t5_2qh6p491
100.0%
2021-01-12T20:52:56.015256image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:56.070146image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
t5_2qh6p491
100.0%

Most occurring characters

ValueCountFrequency (%)
t491
12.5%
5491
12.5%
_491
12.5%
2491
12.5%
q491
12.5%
h491
12.5%
6491
12.5%
p491
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1964
50.0%
Decimal Number1473
37.5%
Connector Punctuation491
 
12.5%

Most frequent character per category

ValueCountFrequency (%)
t491
25.0%
q491
25.0%
h491
25.0%
p491
25.0%
ValueCountFrequency (%)
5491
33.3%
2491
33.3%
6491
33.3%
ValueCountFrequency (%)
_491
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1964
50.0%
Common1964
50.0%

Most frequent character per script

ValueCountFrequency (%)
t491
25.0%
q491
25.0%
h491
25.0%
p491
25.0%
ValueCountFrequency (%)
5491
25.0%
_491
25.0%
2491
25.0%
6491
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3928
100.0%

Most frequent character per block

ValueCountFrequency (%)
t491
12.5%
5491
12.5%
_491
12.5%
2491
12.5%
q491
12.5%
h491
12.5%
6491
12.5%
p491
12.5%

mod_reason_by
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

removal_reason
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

link_flair_background_color
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
491 

Length

Max length0
Median length0
Mean length0
Min length0

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
491
100.0%
2021-01-12T20:52:56.207775image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:56.261632image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

id
Categorical

UNIQUE

Distinct491
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
kvf47p
 
1
kvkc89
 
1
kv84jr
 
1
kv7n6v
 
1
kuvbb3
 
1
Other values (486)
486 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters2946
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique491 ?
Unique (%)100.0%

Sample

1st rowkvh1is
2nd rowkvbi43
3rd rowkvhyq3
4th rowkvfouq
5th rowkv8utu
ValueCountFrequency (%)
kvf47p1
 
0.2%
kvkc891
 
0.2%
kv84jr1
 
0.2%
kv7n6v1
 
0.2%
kuvbb31
 
0.2%
kurbuh1
 
0.2%
kv27wv1
 
0.2%
kusnkm1
 
0.2%
kurq4z1
 
0.2%
kuq4fy1
 
0.2%
Other values (481)481
98.0%
2021-01-12T20:52:56.433172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
kvf47p1
 
0.2%
kvkc891
 
0.2%
kv84jr1
 
0.2%
kv7n6v1
 
0.2%
kuvbb31
 
0.2%
kurbuh1
 
0.2%
kv27wv1
 
0.2%
kusnkm1
 
0.2%
kurq4z1
 
0.2%
kuq4fy1
 
0.2%
Other values (481)481
98.0%

Most occurring characters

ValueCountFrequency (%)
k552
18.7%
v370
 
12.6%
u211
 
7.2%
575
 
2.5%
j67
 
2.3%
e67
 
2.3%
c64
 
2.2%
764
 
2.2%
664
 
2.2%
359
 
2.0%
Other values (26)1353
45.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2363
80.2%
Decimal Number583
 
19.8%

Most frequent character per category

ValueCountFrequency (%)
k552
23.4%
v370
15.7%
u211
 
8.9%
j67
 
2.8%
e67
 
2.8%
c64
 
2.7%
t59
 
2.5%
q58
 
2.5%
l57
 
2.4%
b56
 
2.4%
Other values (16)802
33.9%
ValueCountFrequency (%)
575
12.9%
764
11.0%
664
11.0%
359
10.1%
458
9.9%
958
9.9%
857
9.8%
152
8.9%
251
8.7%
045
7.7%

Most occurring scripts

ValueCountFrequency (%)
Latin2363
80.2%
Common583
 
19.8%

Most frequent character per script

ValueCountFrequency (%)
k552
23.4%
v370
15.7%
u211
 
8.9%
j67
 
2.8%
e67
 
2.8%
c64
 
2.7%
t59
 
2.5%
q58
 
2.5%
l57
 
2.4%
b56
 
2.4%
Other values (16)802
33.9%
ValueCountFrequency (%)
575
12.9%
764
11.0%
664
11.0%
359
10.1%
458
9.9%
958
9.9%
857
9.8%
152
8.9%
251
8.7%
045
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII2946
100.0%

Most frequent character per block

ValueCountFrequency (%)
k552
18.7%
v370
 
12.6%
u211
 
7.2%
575
 
2.5%
j67
 
2.3%
e67
 
2.3%
c64
 
2.2%
764
 
2.2%
664
 
2.2%
359
 
2.0%
Other values (26)1353
45.9%

is_robot_indexable
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
True
491 
ValueCountFrequency (%)
True491
100.0%
2021-01-12T20:52:56.489023image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

report_reasons
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

author
Categorical

HIGH CARDINALITY

Distinct171
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Winterhold2000
53 
f1sh98
45 
guanaco55
 
23
canfbar
 
15
JesusCumelette
 
14
Other values (166)
341 

Length

Max length20
Median length10
Mean length10.88187373
Min length4

Characters and Unicode

Total characters5343
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)23.0%

Sample

1st rowWinterhold2000
2nd rowWinterhold2000
3rd rowCyclones92
4th rownimobo
5th rowWinterhold2000
ValueCountFrequency (%)
Winterhold200053
 
10.8%
f1sh9845
 
9.2%
guanaco5523
 
4.7%
canfbar15
 
3.1%
JesusCumelette14
 
2.9%
nimobo14
 
2.9%
XIIXOO12
 
2.4%
nobody6511
 
2.2%
ChunkyArsenio10
 
2.0%
Foubar_ghost10
 
2.0%
Other values (161)284
57.8%
2021-01-12T20:52:56.688493image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
winterhold200053
 
10.8%
f1sh9845
 
9.2%
guanaco5523
 
4.7%
canfbar15
 
3.1%
nimobo14
 
2.9%
jesuscumelette14
 
2.9%
xiixoo12
 
2.4%
nobody6511
 
2.2%
mohecan10
 
2.0%
foubar_ghost10
 
2.0%
Other values (161)284
57.8%

Most occurring characters

ValueCountFrequency (%)
e419
 
7.8%
o363
 
6.8%
n338
 
6.3%
a316
 
5.9%
i298
 
5.6%
r289
 
5.4%
t255
 
4.8%
s245
 
4.6%
l219
 
4.1%
h196
 
3.7%
Other values (54)2405
45.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4052
75.8%
Decimal Number685
 
12.8%
Uppercase Letter543
 
10.2%
Connector Punctuation39
 
0.7%
Dash Punctuation24
 
0.4%

Most frequent character per category

ValueCountFrequency (%)
W62
 
11.4%
C60
 
11.0%
O37
 
6.8%
T36
 
6.6%
I36
 
6.6%
F34
 
6.3%
A26
 
4.8%
S25
 
4.6%
X24
 
4.4%
B23
 
4.2%
Other values (16)180
33.1%
ValueCountFrequency (%)
e419
 
10.3%
o363
 
9.0%
n338
 
8.3%
a316
 
7.8%
i298
 
7.4%
r289
 
7.1%
t255
 
6.3%
s245
 
6.0%
l219
 
5.4%
h196
 
4.8%
Other values (16)1114
27.5%
ValueCountFrequency (%)
0183
26.7%
182
12.0%
280
11.7%
580
11.7%
969
 
10.1%
859
 
8.6%
446
 
6.7%
634
 
5.0%
733
 
4.8%
319
 
2.8%
ValueCountFrequency (%)
_39
100.0%
ValueCountFrequency (%)
-24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4595
86.0%
Common748
 
14.0%

Most frequent character per script

ValueCountFrequency (%)
e419
 
9.1%
o363
 
7.9%
n338
 
7.4%
a316
 
6.9%
i298
 
6.5%
r289
 
6.3%
t255
 
5.5%
s245
 
5.3%
l219
 
4.8%
h196
 
4.3%
Other values (42)1657
36.1%
ValueCountFrequency (%)
0183
24.5%
182
11.0%
280
10.7%
580
10.7%
969
 
9.2%
859
 
7.9%
446
 
6.1%
_39
 
5.2%
634
 
4.5%
733
 
4.4%
Other values (2)43
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII5343
100.0%

Most frequent character per block

ValueCountFrequency (%)
e419
 
7.8%
o363
 
6.8%
n338
 
6.3%
a316
 
5.9%
i298
 
5.6%
r289
 
5.4%
t255
 
4.8%
s245
 
4.6%
l219
 
4.1%
h196
 
3.7%
Other values (54)2405
45.0%

discussion_type
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing491
Missing (%)100.0%
Memory size4.0 KiB

num_comments
Real number (ℝ≥0)

ZEROS

Distinct152
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.98574338
Minimum0
Maximum1608
Zeros12
Zeros (%)2.4%
Memory size3.8 KiB
2021-01-12T20:52:56.800190image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.5
Q19
median21
Q356.5
95-th percentile342
Maximum1608
Range1608
Interquartile range (IQR)47.5

Descriptive statistics

Standard deviation170.2325834
Coefficient of variation (CV)2.270199317
Kurtosis31.12025859
Mean74.98574338
Median Absolute Deviation (MAD)15
Skewness4.969739313
Sum36818
Variance28979.13245
MonotocityNot monotonic
2021-01-12T20:52:56.905907image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
817
 
3.5%
1416
 
3.3%
216
 
3.3%
315
 
3.1%
1615
 
3.1%
1114
 
2.9%
1514
 
2.9%
113
 
2.6%
413
 
2.6%
1712
 
2.4%
Other values (142)346
70.5%
ValueCountFrequency (%)
012
2.4%
113
2.6%
216
3.3%
315
3.1%
413
2.6%
ValueCountFrequency (%)
16081
0.2%
14821
0.2%
11431
0.2%
9761
0.2%
9271
0.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size491.0 B
True
363 
False
128 
ValueCountFrequency (%)
True363
73.9%
False128
 
26.1%
2021-01-12T20:52:56.988686image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

whitelist_status
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
some_ads
491 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters3928
Distinct characters7
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowsome_ads
2nd rowsome_ads
3rd rowsome_ads
4th rowsome_ads
5th rowsome_ads
ValueCountFrequency (%)
some_ads491
100.0%
2021-01-12T20:52:57.321795image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:57.376650image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
some_ads491
100.0%

Most occurring characters

ValueCountFrequency (%)
s982
25.0%
o491
12.5%
m491
12.5%
e491
12.5%
_491
12.5%
a491
12.5%
d491
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3437
87.5%
Connector Punctuation491
 
12.5%

Most frequent character per category

ValueCountFrequency (%)
s982
28.6%
o491
14.3%
m491
14.3%
e491
14.3%
a491
14.3%
d491
14.3%
ValueCountFrequency (%)
_491
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3437
87.5%
Common491
 
12.5%

Most frequent character per script

ValueCountFrequency (%)
s982
28.6%
o491
14.3%
m491
14.3%
e491
14.3%
a491
14.3%
d491
14.3%
ValueCountFrequency (%)
_491
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3928
100.0%

Most frequent character per block

ValueCountFrequency (%)
s982
25.0%
o491
12.5%
m491
12.5%
e491
12.5%
_491
12.5%
a491
12.5%
d491
12.5%

contest_mode
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:57.403576image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

mod_reports
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size4.0 KiB

author_patreon_flair
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:57.430504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

author_flair_text_color
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)0.6%
Missing152
Missing (%)31.0%
Memory size3.8 KiB
dark
336 
 
3

Length

Max length4
Median length4
Mean length3.66598778
Min length0

Characters and Unicode

Total characters1800
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowdark
2nd rowdark
3rd rownan
4th rownan
5th rowdark
ValueCountFrequency (%)
dark336
68.4%
3
 
0.6%
(Missing)152
31.0%
2021-01-12T20:52:57.589053image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:57.657897image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
dark336
68.9%
nan152
31.1%

Most occurring characters

ValueCountFrequency (%)
a488
27.1%
d336
18.7%
r336
18.7%
k336
18.7%
n304
16.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1800
100.0%

Most frequent character per category

ValueCountFrequency (%)
a488
27.1%
d336
18.7%
r336
18.7%
k336
18.7%
n304
16.9%

Most occurring scripts

ValueCountFrequency (%)
Latin1800
100.0%

Most frequent character per script

ValueCountFrequency (%)
a488
27.1%
d336
18.7%
r336
18.7%
k336
18.7%
n304
16.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII1800
100.0%

Most frequent character per block

ValueCountFrequency (%)
a488
27.1%
d336
18.7%
r336
18.7%
k336
18.7%
n304
16.9%

permalink
Path

UNIQUE

Distinct491
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
/r/Conservative/comments/kvak0l/ron_paul_banned_from_facebook/
 
1
/r/Conservative/comments/kv8yj8/thats_a_hell_of_a_pivot_andrew_cuomos_sudden/
 
1
/r/Conservative/comments/kvawcc/joe_biden_pledges_to_defeat_the_nra/
 
1
/r/Conservative/comments/kvlh0u/biden_says_his_priority_will_be_minority_and/
 
1
/r/Conservative/comments/kv9uws/idaho_internet_company_blocks_facebook_twitter/
 
1
Other values (486)
486 

Length

Max length83
Median length79
Mean length78.01221996
Min length48

Characters and Unicode

Total characters38304
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique491 ?
Unique (%)100.0%

Sample

1st row/r/Conservative/comments/kvh1is/parler_finds_refuge_with_rightleaning_webhosting/
2nd row/r/Conservative/comments/kvbi43/elon_musk_a_lot_of_people_are_going_to_be_super/
3rd row/r/Conservative/comments/kvhyq3/sorry_cleveland/
4th row/r/Conservative/comments/kvfouq/democrat_law_professor_trump_never_actually/
5th row/r/Conservative/comments/kv8utu/elon_musk_advises_people_to_ditch_facebook_and/
ValueCountFrequency (%)
/r/Conservative/comments/kvak0l/ron_paul_banned_from_facebook/1
 
0.2%
/r/Conservative/comments/kv8yj8/thats_a_hell_of_a_pivot_andrew_cuomos_sudden/1
 
0.2%
/r/Conservative/comments/kvawcc/joe_biden_pledges_to_defeat_the_nra/1
 
0.2%
/r/Conservative/comments/kvlh0u/biden_says_his_priority_will_be_minority_and/1
 
0.2%
/r/Conservative/comments/kv9uws/idaho_internet_company_blocks_facebook_twitter/1
 
0.2%
/r/Conservative/comments/kvitu1/the_ghost_who_votes/1
 
0.2%
/r/Conservative/comments/kun0sc/forbes_were_holding_those_who_lied_for_trump/1
 
0.2%
/r/Conservative/comments/kv70z5/pbs_dan_rather_discusses_the_prevalence_of/1
 
0.2%
/r/Conservative/comments/kv5xyo/trump_not_resigning_will_not_leave_the_public/1
 
0.2%
/r/Conservative/comments/kup8j2/sen_joe_manchin_is_open_to_statehood_for_dc/1
 
0.2%
Other values (481)481
98.0%
2021-01-12T20:52:57.854370image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
r/conservative/comments/ktqqk1/cnn_calls_tucker_carlson_a_parasite_over_his1
 
0.2%
r/conservative/comments/kv2i0b/an_open_letter_to_sen_joe_manchin_its_time_to1
 
0.2%
r/conservative/comments/kuinwv/justin_amashs_replacement_grew_up_watching_the1
 
0.2%
r/conservative/comments/kvjipx/belichick_rejects_medal_of_freedom_from_trump1
 
0.2%
r/conservative/comments/kvbxue/navarro_trump_itching_to_defend_himself_against1
 
0.2%
r/conservative/comments/kuuk2j/report_trump_will_take_on_big_tech_in_final_days1
 
0.2%
r/conservative/comments/kvivg4/fascism_comes_to_the_us_yes_its_a_woke_fascism_of1
 
0.2%
r/conservative/comments/ku2kq4/lincoln_project_says_it_is_building_database_of1
 
0.2%
r/conservative/comments/kup3kj/trump_orders_flags_halfstaff_for_capitol_police1
 
0.2%
r/conservative/comments/kuronr/breaking_pelosi_gives_pence_24hrs_to_activate1
 
0.2%
Other values (481)481
98.0%

Most occurring characters

ValueCountFrequency (%)
e3642
 
9.5%
_3103
 
8.1%
/2946
 
7.7%
t2609
 
6.8%
o2563
 
6.7%
s2426
 
6.3%
r2391
 
6.2%
n2260
 
5.9%
a2003
 
5.2%
i1874
 
4.9%
Other values (29)12487
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter31019
81.0%
Connector Punctuation3103
 
8.1%
Other Punctuation2946
 
7.7%
Decimal Number745
 
1.9%
Uppercase Letter491
 
1.3%

Most frequent character per category

ValueCountFrequency (%)
e3642
11.7%
t2609
 
8.4%
o2563
 
8.3%
s2426
 
7.8%
r2391
 
7.7%
n2260
 
7.3%
a2003
 
6.5%
i1874
 
6.0%
m1632
 
5.3%
v1552
 
5.0%
Other values (16)8067
26.0%
ValueCountFrequency (%)
094
12.6%
593
12.5%
285
11.4%
179
10.6%
771
9.5%
969
9.3%
669
9.3%
364
8.6%
861
8.2%
460
8.1%
ValueCountFrequency (%)
/2946
100.0%
ValueCountFrequency (%)
C491
100.0%
ValueCountFrequency (%)
_3103
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin31510
82.3%
Common6794
 
17.7%

Most frequent character per script

ValueCountFrequency (%)
e3642
11.6%
t2609
 
8.3%
o2563
 
8.1%
s2426
 
7.7%
r2391
 
7.6%
n2260
 
7.2%
a2003
 
6.4%
i1874
 
5.9%
m1632
 
5.2%
v1552
 
4.9%
Other values (17)8558
27.2%
ValueCountFrequency (%)
_3103
45.7%
/2946
43.4%
094
 
1.4%
593
 
1.4%
285
 
1.3%
179
 
1.2%
771
 
1.0%
969
 
1.0%
669
 
1.0%
364
 
0.9%
Other values (2)121
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII38304
100.0%

Most frequent character per block

ValueCountFrequency (%)
e3642
 
9.5%
_3103
 
8.1%
/2946
 
7.7%
t2609
 
6.8%
o2563
 
6.7%
s2426
 
6.3%
r2391
 
6.2%
n2260
 
5.9%
a2003
 
5.2%
i1874
 
4.9%
Other values (29)12487
32.6%
Common prefix\r\Conservative\comments\k
Unique stems487
Unique names487
Unique extensions1
Unique directories491
Unique anchors1
ValueCountFrequency (%)
/r/Conservative/comments/kvak0l/ron_paul_banned_from_facebook/1
 
0.2%
/r/Conservative/comments/kv8yj8/thats_a_hell_of_a_pivot_andrew_cuomos_sudden/1
 
0.2%
/r/Conservative/comments/kvawcc/joe_biden_pledges_to_defeat_the_nra/1
 
0.2%
/r/Conservative/comments/kvlh0u/biden_says_his_priority_will_be_minority_and/1
 
0.2%
/r/Conservative/comments/kv9uws/idaho_internet_company_blocks_facebook_twitter/1
 
0.2%
/r/Conservative/comments/kvitu1/the_ghost_who_votes/1
 
0.2%
/r/Conservative/comments/kun0sc/forbes_were_holding_those_who_lied_for_trump/1
 
0.2%
/r/Conservative/comments/kv70z5/pbs_dan_rather_discusses_the_prevalence_of/1
 
0.2%
/r/Conservative/comments/kv5xyo/trump_not_resigning_will_not_leave_the_public/1
 
0.2%
/r/Conservative/comments/kup8j2/sen_joe_manchin_is_open_to_statehood_for_dc/1
 
0.2%
Other values (481)481
98.0%
ValueCountFrequency (%)
idaho_internet_company_blocks_facebook_twitter2
 
0.4%
republican_blocks_house_from_bringing_up_25th2
 
0.4%
fbi_internal_memo_warns_of_plans_for_armed2
 
0.4%
russian_dissident_alexei_navalny_rebukes_twitter2
 
0.4%
pompeo_defends_trump_says_people_walking_away1
 
0.2%
several_us_capitol_officers_were_suspended_after1
 
0.2%
pritzker_wants_500m_tax_hike_on_illinois_small1
 
0.2%
house_majority_whip_wants_investigation_into_how1
 
0.2%
scummy_tech_bro_twitter_ceo_mocks_parlers_removal1
 
0.2%
the_progressive_purge_begins_techs_stampede1
 
0.2%
Other values (477)477
97.1%
ValueCountFrequency (%)
idaho_internet_company_blocks_facebook_twitter2
 
0.4%
republican_blocks_house_from_bringing_up_25th2
 
0.4%
fbi_internal_memo_warns_of_plans_for_armed2
 
0.4%
russian_dissident_alexei_navalny_rebukes_twitter2
 
0.4%
pompeo_defends_trump_says_people_walking_away1
 
0.2%
several_us_capitol_officers_were_suspended_after1
 
0.2%
pritzker_wants_500m_tax_hike_on_illinois_small1
 
0.2%
house_majority_whip_wants_investigation_into_how1
 
0.2%
scummy_tech_bro_twitter_ceo_mocks_parlers_removal1
 
0.2%
the_progressive_purge_begins_techs_stampede1
 
0.2%
Other values (477)477
97.1%
ValueCountFrequency (%)
491
100.0%
ValueCountFrequency (%)
\r\Conservative\comments\kvaxms1
 
0.2%
\r\Conservative\comments\kv5w5s1
 
0.2%
\r\Conservative\comments\kuwjge1
 
0.2%
\r\Conservative\comments\kujzkw1
 
0.2%
\r\Conservative\comments\kv5zpt1
 
0.2%
\r\Conservative\comments\kvbmc81
 
0.2%
\r\Conservative\comments\kv5vj61
 
0.2%
\r\Conservative\comments\kv2g901
 
0.2%
\r\Conservative\comments\kunbni1
 
0.2%
\r\Conservative\comments\kv5vnw1
 
0.2%
Other values (481)481
98.0%
ValueCountFrequency (%)
\491
100.0%

parent_whitelist_status
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
some_ads
491 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters3928
Distinct characters7
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowsome_ads
2nd rowsome_ads
3rd rowsome_ads
4th rowsome_ads
5th rowsome_ads
ValueCountFrequency (%)
some_ads491
100.0%
2021-01-12T20:52:58.034912image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:58.089773image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
some_ads491
100.0%

Most occurring characters

ValueCountFrequency (%)
s982
25.0%
o491
12.5%
m491
12.5%
e491
12.5%
_491
12.5%
a491
12.5%
d491
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3437
87.5%
Connector Punctuation491
 
12.5%

Most frequent character per category

ValueCountFrequency (%)
s982
28.6%
o491
14.3%
m491
14.3%
e491
14.3%
a491
14.3%
d491
14.3%
ValueCountFrequency (%)
_491
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3437
87.5%
Common491
 
12.5%

Most frequent character per script

ValueCountFrequency (%)
s982
28.6%
o491
14.3%
m491
14.3%
e491
14.3%
a491
14.3%
d491
14.3%
ValueCountFrequency (%)
_491
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3928
100.0%

Most frequent character per block

ValueCountFrequency (%)
s982
25.0%
o491
12.5%
m491
12.5%
e491
12.5%
_491
12.5%
a491
12.5%
d491
12.5%

stickied
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:58.116704image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

url
URL

Distinct488
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
https://www.foxnews.com/politics/fbi-internal-memo-warns-of-plans-for-armed-protests-in-all-50-state-capitals-ahead-of-biden-inauguration
 
2
https://www.oann.com/joe-biden-pledges-to-defeat-the-nra/
 
2
https://thefederalist.com/2021/01/11/left-wing-terrorists-bombed-the-senate-in-1983-bill-clinton-let-them-out-of-prison-early-at-jerry-nadlers-request/
 
2
https://deadline.com/2021/01/nbc-sports-benches-nhl-analyst-mike-milbury-stanley-cup-playoffs-insulting-comments-about-women-1203020857/
 
1
https://www.supremecourt.gov/opinions/16pdf/15-1194_08l1.pdf
 
1
Other values (483)
483 
ValueCountFrequency (%)
https://www.foxnews.com/politics/fbi-internal-memo-warns-of-plans-for-armed-protests-in-all-50-state-capitals-ahead-of-biden-inauguration2
 
0.4%
https://www.oann.com/joe-biden-pledges-to-defeat-the-nra/2
 
0.4%
https://thefederalist.com/2021/01/11/left-wing-terrorists-bombed-the-senate-in-1983-bill-clinton-let-them-out-of-prison-early-at-jerry-nadlers-request/2
 
0.4%
https://deadline.com/2021/01/nbc-sports-benches-nhl-analyst-mike-milbury-stanley-cup-playoffs-insulting-comments-about-women-1203020857/1
 
0.2%
https://www.supremecourt.gov/opinions/16pdf/15-1194_08l1.pdf1
 
0.2%
https://www.theepochtimes.com/missouri-court-rejects-st-louis-prosecutors-appeal-in-mccloskey-case_3650523.html1
 
0.2%
https://globalnews.ca/news/7567802/trump-resign-pressure-supporters/1
 
0.2%
https://www.newsmax.com/us/d-c-trump-biden-capitol/2021/01/11/id/1005169/1
 
0.2%
https://www.newsmax.com/politics/cancel-culture-stripe-payments-online/2021/01/10/id/1005008/1
 
0.2%
https://www.dailymail.co.uk/news/article-9134819/Group-demands-ethics-inquiry-GOPs-Mo-Brooks-speech-rally-prompted-Capitol-siege.html1
 
0.2%
Other values (478)478
97.4%
ValueCountFrequency (%)
https482
98.2%
http9
 
1.8%
ValueCountFrequency (%)
www.theepochtimes.com39
 
7.9%
www.foxnews.com28
 
5.7%
www.breitbart.com27
 
5.5%
www.dailywire.com24
 
4.9%
www.dailymail.co.uk19
 
3.9%
redstate.com15
 
3.1%
www.wsj.com15
 
3.1%
townhall.com12
 
2.4%
babylonbee.com12
 
2.4%
www.washingtonexaminer.com12
 
2.4%
Other values (140)288
58.7%
ValueCountFrequency (%)
/articles/the-progressive-purge-begins-116103193764
 
0.8%
/watch3
 
0.6%
/2021/01/10/twitter-hasnt-suspended-these-accounts-or-tweets-that-openly-incite-violence/2
 
0.4%
/republican-blocks-house-from-bringing-up-25th-amendment-bill_3652031.html2
 
0.4%
/twitter-shares-drop-by-12-percent-after-company-banned-trump_3652172.html2
 
0.4%
/russian-dissident-alexei-navalny-rebukes-twitter-for-censorship-of-trump_3651945.html2
 
0.4%
/aclu-warns-of-unchecked-power-after-facebook-twitter-suspend-trump_3650715.html2
 
0.4%
/potus-cut-off-supporters-even-email-company-suspends-trumps-service/2
 
0.4%
/joe-biden-pledges-to-defeat-the-nra/2
 
0.4%
/news/articles/2021-01-11/merkel-sees-closing-trump-s-social-media-accounts-problematic2
 
0.4%
Other values (462)468
95.3%
ValueCountFrequency (%)
440
89.6%
utm_source=news&amp;utm_medium=reddit&amp;utm_campaign=breaking-2021-01-11-22
 
0.4%
mod=hp_opin_pos_1&amp;fbclid=IwAR2Wbd6TXRo02cmyHxiCTeVp0S9qSsStU04q5M0bSnkueyYBWmj318dfs-k1
 
0.2%
v=pOmXiapfCs81
 
0.2%
utm_source=feedburner&amp;utm_medium=feed&amp;utm_campaign=Feed%3A+breitbart+%28Breitbart+News%291
 
0.2%
fbclid=IwAR2-dHT4Ls_3JJXbUGiOhckNNoc1U2XiUcKYXE-u0djMDB0MCUQ4W0uFIEo1
 
0.2%
cmpid=socialflow-twitter-business&amp;utm_source=twitter&amp;utm_medium=social&amp;utm_content=business&amp;utm_campaign=socialflow-organic1
 
0.2%
utm_source=justthenews.com&amp;amp;utm_medium=feed&amp;amp;utm_campaign=external-news-aggregators1
 
0.2%
sh=2d3f1b302d461
 
0.2%
sh=5451ab5cf6991
 
0.2%
Other values (41)41
 
8.4%
ValueCountFrequency (%)
487
99.2%
&amp;_intcmp=hp1bt3,hp1bt1
 
0.2%
processed1
 
0.2%
038;utm_medium=conservativetribune&amp;#038;utm_campaign=parler1
 
0.2%
comment1
 
0.2%
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
632489
264 
632488
205 
632487
 
22

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters2946
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row632488
2nd row632488
3rd row632488
4th row632488
5th row632488
ValueCountFrequency (%)
632489264
53.8%
632488205
41.8%
63248722
 
4.5%
2021-01-12T20:52:58.266309image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:58.322152image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
632489264
53.8%
632488205
41.8%
63248722
 
4.5%

Most occurring characters

ValueCountFrequency (%)
8696
23.6%
6491
16.7%
3491
16.7%
2491
16.7%
4491
16.7%
9264
 
9.0%
722
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2946
100.0%

Most frequent character per category

ValueCountFrequency (%)
8696
23.6%
6491
16.7%
3491
16.7%
2491
16.7%
4491
16.7%
9264
 
9.0%
722
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common2946
100.0%

Most frequent character per script

ValueCountFrequency (%)
8696
23.6%
6491
16.7%
3491
16.7%
2491
16.7%
4491
16.7%
9264
 
9.0%
722
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII2946
100.0%

Most frequent character per block

ValueCountFrequency (%)
8696
23.6%
6491
16.7%
3491
16.7%
2491
16.7%
4491
16.7%
9264
 
9.0%
722
 
0.7%

created_utc
Real number (ℝ≥0)

HIGH CORRELATION

Distinct490
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1610362127
Minimum1610197696
Maximum1610453734
Zeros0
Zeros (%)0.0%
Memory size3.8 KiB
2021-01-12T20:52:58.405927image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1610197696
5-th percentile1610247692
Q11610320575
median1610383022
Q31610400038
95-th percentile1610424233
Maximum1610453734
Range256038
Interquartile range (IQR)79463

Descriptive statistics

Standard deviation54841.2184
Coefficient of variation (CV)3.405520875 × 105
Kurtosis0.2141099265
Mean1610362127
Median Absolute Deviation (MAD)25638
Skewness-1.00138612
Sum7.906878044 × 1011
Variance3007559235
MonotocityNot monotonic
2021-01-12T20:52:58.518624image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16103808192
 
0.4%
16103099371
 
0.2%
16103888491
 
0.2%
16103041161
 
0.2%
16103834061
 
0.2%
16104176281
 
0.2%
16103960231
 
0.2%
16103768561
 
0.2%
16104219301
 
0.2%
16104083171
 
0.2%
Other values (480)480
97.8%
ValueCountFrequency (%)
16101976961
0.2%
16101981371
0.2%
16102075311
0.2%
16102090581
0.2%
16102101951
0.2%
ValueCountFrequency (%)
16104537341
0.2%
16104522451
0.2%
16104468671
0.2%
16104456971
0.2%
16104427991
0.2%

num_crossposts
Real number (ℝ≥0)

ZEROS

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2260692464
Minimum0
Maximum6
Zeros417
Zeros (%)84.9%
Memory size3.8 KiB
2021-01-12T20:52:58.612375image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6879521721
Coefficient of variation (CV)3.043103752
Kurtosis28.77555948
Mean0.2260692464
Median Absolute Deviation (MAD)0
Skewness4.770870437
Sum111
Variance0.4732781911
MonotocityNot monotonic
2021-01-12T20:52:58.686178image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0417
84.9%
155
 
11.2%
212
 
2.4%
54
 
0.8%
32
 
0.4%
61
 
0.2%
ValueCountFrequency (%)
0417
84.9%
155
 
11.2%
212
 
2.4%
32
 
0.4%
54
 
0.8%
ValueCountFrequency (%)
61
 
0.2%
54
 
0.8%
32
 
0.4%
212
 
2.4%
155
11.2%

media
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing488
Missing (%)99.4%
Memory size4.0 KiB

is_video
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size491.0 B
False
491 
ValueCountFrequency (%)
False491
100.0%
2021-01-12T20:52:58.752002image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

link_flair_template_id
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)42.9%
Missing484
Missing (%)98.6%
Memory size3.8 KiB
3cbf370a-5fe4-11e6-9198-0e0b7c2c3ef3
1ad56728-2771-11e6-8d92-0e4ee7c21d2d
4defb91e-0355-11eb-9c9e-0eb32694eab3

Length

Max length36
Median length3
Mean length3.470468432
Min length3

Characters and Unicode

Total characters1704
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)28.6%

Sample

1st rownan
2nd rownan
3rd row3cbf370a-5fe4-11e6-9198-0e0b7c2c3ef3
4th rownan
5th rownan
ValueCountFrequency (%)
3cbf370a-5fe4-11e6-9198-0e0b7c2c3ef35
 
1.0%
1ad56728-2771-11e6-8d92-0e4ee7c21d2d1
 
0.2%
4defb91e-0355-11eb-9c9e-0eb32694eab31
 
0.2%
(Missing)484
98.6%
2021-01-12T20:52:58.923543image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T20:52:58.985377image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
nan484
98.6%
3cbf370a-5fe4-11e6-9198-0e0b7c2c3ef35
 
1.0%
1ad56728-2771-11e6-8d92-0e4ee7c21d2d1
 
0.2%
4defb91e-0355-11eb-9c9e-0eb32694eab31
 
0.2%

Most occurring characters

ValueCountFrequency (%)
n968
56.8%
a491
28.8%
e30
 
1.8%
-28
 
1.6%
323
 
1.3%
123
 
1.3%
018
 
1.1%
c17
 
1.0%
f16
 
0.9%
915
 
0.9%
Other values (8)75
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1541
90.4%
Decimal Number135
 
7.9%
Dash Punctuation28
 
1.6%

Most frequent character per category

ValueCountFrequency (%)
323
17.0%
123
17.0%
018
13.3%
915
11.1%
714
10.4%
211
8.1%
58
 
5.9%
48
 
5.9%
68
 
5.9%
87
 
5.2%
ValueCountFrequency (%)
n968
62.8%
a491
31.9%
e30
 
1.9%
c17
 
1.1%
f16
 
1.0%
b14
 
0.9%
d5
 
0.3%
ValueCountFrequency (%)
-28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1541
90.4%
Common163
 
9.6%

Most frequent character per script

ValueCountFrequency (%)
-28
17.2%
323
14.1%
123
14.1%
018
11.0%
915
9.2%
714
8.6%
211
 
6.7%
58
 
4.9%
48
 
4.9%
68
 
4.9%
ValueCountFrequency (%)
n968
62.8%
a491
31.9%
e30
 
1.9%
c17
 
1.1%
f16
 
1.0%
b14
 
0.9%
d5
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1704
100.0%

Most frequent character per block

ValueCountFrequency (%)
n968
56.8%
a491
28.8%
e30
 
1.8%
-28
 
1.6%
323
 
1.3%
123
 
1.3%
018
 
1.1%
c17
 
1.0%
f16
 
0.9%
915
 
0.9%
Other values (8)75
 
4.4%

is_gallery
Boolean

MISSING

Distinct1
Distinct (%)50.0%
Missing489
Missing (%)99.6%
Memory size3.8 KiB
True
 
2
(Missing)
489 
ValueCountFrequency (%)
True2
 
0.4%
(Missing)489
99.6%
2021-01-12T20:52:59.040235image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

media_metadata
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing489
Missing (%)99.6%
Memory size4.0 KiB

gallery_data
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing489
Missing (%)99.6%
Memory size4.0 KiB

Interactions

2021-01-12T20:52:27.142962image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:27.260198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:27.353947image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:27.514530image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:27.607282image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:27.710007image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:27.802759image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:27.905484image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:28.002225image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:28.095974image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:28.190721image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:28.302423image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:28.411132image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:28.510372image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:28.620078image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:28.719812image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:28.827523image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:28.930249image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:29.029982image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:29.135699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:29.246403image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:29.378051image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:29.486760image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:29.606440image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:29.715149image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:29.835826image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:29.948525image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:30.059229image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:30.151981image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:30.249719image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:30.358428image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:30.467138image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:30.573852image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:30.673585image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:30.852108image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:30.952839image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:31.051574image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:31.157292image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:31.266998image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:31.385681image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:31.494390image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:31.625040image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:31.733749image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:31.853430image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:31.966128image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:32.076832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:32.169584image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:32.267323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:32.375035image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:32.470778image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:32.575743image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:32.683455image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:32.789204image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:32.888212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:32.983956image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:33.085686image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:33.192401image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:33.309087image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:33.414804image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:33.531492image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:33.638206image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:33.764870image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:33.875139image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:33.982851image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:34.077598image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:34.176336image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:34.285050image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:34.383779image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:34.494483image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:34.593219image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:34.700933image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:34.905946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:35.012631image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:35.110395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:35.213096image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:35.324381image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:35.424141image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:35.531859image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:35.629592image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:35.737334image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:35.840059image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2021-01-12T20:52:59.139964image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-01-12T20:52:59.599734image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-01-12T20:53:00.063559image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-01-12T20:53:00.504351image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-01-12T20:53:00.821560image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-01-12T20:52:36.307809image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:44.747459image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:46.958322image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T20:52:47.461975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

approved_at_utcsubredditselftextauthor_fullnamesavedmod_reason_titlegildedclickedtitlelink_flair_richtextsubreddit_name_prefixedhiddenpwlslink_flair_css_classdownsthumbnail_heighttop_awarded_typehide_scorenamequarantinelink_flair_text_colorupvote_ratioauthor_flair_background_colorsubreddit_typeupstotal_awards_receivedmedia_embedthumbnail_widthauthor_flair_template_idis_original_contentuser_reportssecure_mediais_reddit_media_domainis_metacategorysecure_media_embedlink_flair_textcan_mod_postscoreapproved_byauthor_premiumthumbnaileditedauthor_flair_css_classauthor_flair_richtextgildingspost_hintcontent_categoriesis_selfmod_notecreatedlink_flair_typewlsremoved_by_categorybanned_byauthor_flair_typedomainallow_live_commentsselftext_htmllikessuggested_sortbanned_at_utcurl_overridden_by_destview_countarchivedno_followis_crosspostablepinnedover_18previewall_awardingsawardersmedia_onlycan_gildspoilerlockedauthor_flair_texttreatment_tagsvisitedremoved_bynum_reportsdistinguishedsubreddit_idmod_reason_byremoval_reasonlink_flair_background_coloridis_robot_indexablereport_reasonsauthordiscussion_typenum_commentssend_replieswhitelist_statuscontest_modemod_reportsauthor_patreon_flairauthor_flair_text_colorpermalinkparent_whitelist_statusstickiedurlsubreddit_subscriberscreated_utcnum_crosspostsmediais_videolink_flair_template_idis_gallerymedia_metadatagallery_data
0NoneConservativet2_4hgotpz8FalseNone0FalseParler finds refuge with right-leaning webhosting service[{'e': 'text', 't': 'Flaired Users Only'}]r/ConservativeFalse7CONSERVATIVESONLY073.0NoneFalset3_kvh1isFalsedark0.83public17747{}140.0NoneFalse[]NoneFalseFalseNone{}Flaired Users OnlyFalse1774NoneTruehttps://b.thumbs.redditmedia.com/KouUuQMiFYEXbo5UbYqcM0GTCRoKFKVa1ENvS08IQ6k.jpgFalseNone[{'e': 'text', 't': 'Conservative'}]{'gid_1': 3}linkNoneFalseNone1.610443e+09richtext7NoneNonerichtextwashingtonexaminer.comTrueNoneNoneconfidenceNonehttps://www.washingtonexaminer.com/news/parler-finds-refuge-with-right-leaning-webhosting-serviceNoneFalseFalseFalseFalseFalse{'images': [{'source': {'url': 'https://external-preview.redd.it/9ReMgmhvdAvTicj0rNCjL1mGZ6guPX8cjWrpRdzipuI.jpg?auto=webp&amp;s=a96c371128c5d30c66cbde153c6bf6e23d6db767', 'width': 1200, 'height': 630}, 'resolutions': [{'url': 'https://external-preview.redd.it/9ReMgmhvdAvTicj0rNCjL1mGZ6guPX8cjWrpRdzipuI.jpg?width=108&amp;crop=smart&amp;auto=webp&amp;s=2489972790247c611ab246d90b29b3347bc72494', 'width': 108, 'height': 56}, {'url': 'https://external-preview.redd.it/9ReMgmhvdAvTicj0rNCjL1mGZ6guPX8cjWrpRdzipuI.jpg?width=216&amp;crop=smart&amp;auto=webp&amp;s=7731f51c9c31c8f5d109fa0406b8e4fa0e5170e2', 'width': 216, 'height': 113}, {'url': 'https://external-preview.redd.it/9ReMgmhvdAvTicj0rNCjL1mGZ6guPX8cjWrpRdzipuI.jpg?width=320&amp;crop=smart&amp;auto=webp&amp;s=0748344c89462e94aef918da49934deb1fe0453e', 'width': 320, 'height': 168}, {'url': 'https://external-preview.redd.it/9ReMgmhvdAvTicj0rNCjL1mGZ6guPX8cjWrpRdzipuI.jpg?width=640&amp;crop=smart&amp;auto=webp&amp;s=5cf8f4111e1a6ccc79cdc46002ea6e5bba3a22da', 'width': 640, 'height': 336}, {'url': 'https://external-preview.redd.it/9ReMgmhvdAvTicj0rNCjL1mGZ6guPX8cjWrpRdzipuI.jpg?width=960&amp;crop=smart&amp;auto=webp&amp;s=16a27d6086b9c0b87b8acac3c9836363762f367f', 'width': 960, 'height': 504}, {'url': 'https://external-preview.redd.it/9ReMgmhvdAvTicj0rNCjL1mGZ6guPX8cjWrpRdzipuI.jpg?width=1080&amp;crop=smart&amp;auto=webp&amp;s=5a911896260aaab6f5aa14091566e80b90e2c2e5', 'width': 1080, 'height': 567}], 'variants': {}, 'id': 'R_LRfLK7HOMhOqfZ5cGQtm1fjHJf440iny1AlbswZbo'}], 'enabled': False}[{'giver_coin_reward': None, 'subreddit_id': None, 'is_new': False, 'days_of_drip_extension': 0, 'coin_price': 125, 'id': 'award_5f123e3d-4f48-42f4-9c11-e98b566d5897', 'penny_donate': None, 'award_sub_type': 'GLOBAL', 'coin_reward': 0, 'icon_url': 'https://i.redd.it/award_images/t5_22cerq/5izbv4fn0md41_Wholesome.png', 'days_of_premium': 0, 'tiers_by_required_awardings': None, 'resized_icons': [{'url': 'https://preview.redd.it/award_images/t5_22cerq/5izbv4fn0md41_Wholesome.png?width=16&amp;height=16&amp;auto=webp&amp;s=92932f465d58e4c16b12b6eac4ca07d27e3d11c0', 'width': 16, 'height': 16}, {'url': 'https://preview.redd.it/award_images/t5_22cerq/5izbv4fn0md41_Wholesome.png?width=32&amp;height=32&amp;auto=webp&amp;s=d11484a208d68a318bf9d4fcf371171a1cb6a7ef', 'width': 32, 'height': 32}, {'url': 'https://preview.redd.it/award_images/t5_22cerq/5izbv4fn0md41_Wholesome.png?width=48&amp;height=48&amp;auto=webp&amp;s=febdf28b6f39f7da7eb1365325b85e0bb49a9f63', 'width': 48, 'height': 48}, {'url': 'https://preview.redd.it/award_images/t5_22cerq/5izbv4fn0md41_Wholesome.png?width=64&amp;height=64&amp;auto=webp&amp;s=b4406a2d88bf86fa3dc8a45aacf7e0c7bdccc4fb', 'width': 64, 'height': 64}, {'url': 'https://preview.redd.it/award_images/t5_22cerq/5izbv4fn0md41_Wholesome.png?width=128&amp;height=128&amp;auto=webp&amp;s=19555b13e3e196b62eeb9160d1ac1d1b372dcb0b', 'width': 128, 'height': 128}], 'icon_width': 2048, 'static_icon_width': 2048, 'start_date': None, 'is_enabled': True, 'awardings_required_to_grant_benefits': None, 'description': 'When you come across a feel-good thing.', 'end_date': None, 'subreddit_coin_reward': 0, 'count': 2, 'static_icon_height': 2048, 'name': 'Wholesome', 'resized_static_icons': [{'url': 'https://preview.redd.it/award_images/t5_22cerq/5izbv4fn0md41_Wholesome.png?width=16&amp;height=16&amp;auto=webp&amp;s=92932f465d58e4c16b12b6eac4ca07d27e3d11c0', 'width': 16, 'height': 16}, {'url': 'https://preview.redd.it/award_images/t5_22cerq/5izbv4fn0md41_Wholesome.png?width=32&amp;height=32&amp;auto=webp&amp;s=d11484a208d68a318bf9d4fcf371171a1cb6a7ef', 'width': 32, 'height': 32}, {'url': 'https://preview.redd.it/award_images/t5_22cerq/5izbv4fn0md41_Wholesome.png?width=48&amp;height=48&amp;auto=webp&amp;s=febdf28b6f39f7da7eb1365325b85e0bb49a9f63', 'width': 48, 'height': 48}, {'url': 'https://preview.redd.it/award_images/t5_22cerq/5izbv4fn0md41_Wholesome.png?width=64&amp;height=64&amp;auto=webp&amp;s=b4406a2d88bf86fa3dc8a45aacf7e0c7bdccc4fb', 'width': 64, 'height': 64}, {'url': 'https://preview.redd.it/award_images/t5_22cerq/5izbv4fn0md41_Wholesome.png?width=128&amp;height=128&amp;auto=webp&amp;s=19555b13e3e196b62eeb9160d1ac1d1b372dcb0b', 'width': 128, 'height': 128}], 'icon_format': None, 'icon_height': 2048, 'penny_price': None, 'award_type': 'global', 'static_icon_url': 'https://i.redd.it/award_images/t5_22cerq/5izbv4fn0md41_Wholesome.png'}, {'giver_coin_reward': None, 'subreddit_id': None, 'is_new': False, 'days_of_drip_extension': 0, 'coin_price': 100, 'id': 'gid_1', 'penny_donate': None, 'award_sub_type': 'GLOBAL', 'coin_reward': 0, 'icon_url': 'https://www.redditstatic.com/gold/awards/icon/silver_512.png', 'days_of_premium': 0, 'tiers_by_required_awardings': None, 'resized_icons': [{'url': 'https://www.redditstatic.com/gold/awards/icon/silver_16.png', 'width': 16, 'height': 16}, {'url': 'https://www.redditstatic.com/gold/awards/icon/silver_32.png', 'width': 32, 'height': 32}, {'url': 'https://www.redditstatic.com/gold/awards/icon/silver_48.png', 'width': 48, 'height': 48}, {'url': 'https://www.redditstatic.com/gold/awards/icon/silver_64.png', 'width': 64, 'height': 64}, {'url': 'https://www.redditstatic.com/gold/awards/icon/silver_128.png', 'width': 128, 'height': 128}], 'icon_width': 512, 'static_icon_width': 512, 'start_date': None, 'is_enabled': True, 'awardings_required_to_grant_benefits': None, 'description': 'Shows the Silver Award... and that's it.', 'end_date': None, 'subreddit_coin_reward': 0, 'count': 3, 'static_icon_height': 512, 'name': 'Silver', 'resized_static_icons': [{'url': 'https://www.redditstatic.com/gold/awards/icon/silver_16.png', 'width': 16, 'height': 16}, {'url': 'https://www.redditstatic.com/gold/awards/icon/silver_32.png', 'width': 32, 'height': 32}, {'url': 'https://www.redditstatic.com/gold/awards/icon/silver_48.png', 'width': 48, 'height': 48}, {'url': 'https://www.redditstatic.com/gold/awards/icon/silver_64.png', 'width': 64, 'height': 64}, {'url': 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